Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Responsibilities Atlassian is looking for a Senior Data Engineer to join our Data Engineering team which is responsible for building our data lake, maintaining our big data pipelines / services and facilitating the movement of billions of messages each day. We work directly with the business stakeholders and plenty of platform and engineering teams to enable growth and retention strategies at Atlassian. We are looking for an open-minded, structured thinker who is passionate about building services that scale. On a typical day you will help our stakeholder teams ingest data faster into our data lake, you’ll find ways to make our data pipelines more efficient, or even come up ideas to help instigate self-serve data engineering within the company. You’ll get the opportunity to work on a AWS based data lake backed by the full suite of open source projects such as Spark and Airflow. We are a team with little legacy in our tech stack and as a result you’ll spend less time paying off technical debt and more time identifying ways to make our platform better and improve our users experience. Qualifications As a Senior Data Engineer in the DE team, you will have the opportunity to apply your strong technical experience building highly reliable services on managing and orchestrating a multi-petabyte scale data lake. You enjoy working in a fast paced environment and you are able to take vague requirements and transform them into solid solutions. You are motivated by solving challenging problems, where creativity is as crucial as your ability to write code and test cases. On Your First Day, We'll Expect You To Have A BS in Computer Science or equivalent experience At least 7+ years professional experience as a Sr. Software Engineer or Sr. Data Engineer Strong programming skills (Python, Java or Scala preferred) Experience writing SQL, structuring data, and data storage practices Experience with data modeling Knowledge of data warehousing concepts Experience building data pipelines, platforms Experience with Databricks, Spark, Hive, Airflow and other streaming technologies to process incredible volumes of streaming data Experience in modern software development practices (Agile, TDD, CICD) Strong focus on data quality and experience with internal/external tools/frameworks to automatically detect data issues, anomalies. A willingness to accept failure, learn and try again An open mind to try solutions that may seem crazy at first Experience working on Amazon Web Services (in particular using EMR, Kinesis, RDS, S3, SQS and the like) It's Preferred That You Have Experience building self-service tooling and platforms Built and designed Kappa architecture platforms Contributed to open source projects (Ex: Operators in Airflow) Experience with Data Build Tool (DBT) Our Perks & Benefits Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits . About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . Show more Show less

As a Data engineer in the ADC Engineering team, you will: - Work alongside our engineers to help design and build scalable data pipelines while evolving the data surface. Help prove out and productionize Cloud Native Infrastructure and tooling to support scalable data cloud. Have fun as part of an awesome team. Specific Responsibilities: Its a mix of backend application engineering (Python backend) including data engineering to build solution leveraging existing Data Framework Collaborating in a multi-disciplinary squad involving program and product managers, data scientists, and client professionals to expand the product offering based on business impact and demand Be involved from inception of projects, understanding requirements, designing & developing solutions, and incorporating them into the designs of our platforms Maintain excellent knowledge of the technical landscape for data & cloud tooling Assist in troubleshooting issues, support the operation of production software Write technical documentation Required Skills 4+ years of industry experience in data engineering area. Passion for engineering and optimizing data sets, data pipelines and architecture. Ability to build processes that support data transformation, workload management, data structures, lineage, and metadata. Knowledge of SQL and performance tuning. Experience with Snowflake is preferred. Good working knowledge languages such as Python/Java Understanding of software deployment and orchestration technologies such as airflow etc. Experience in creating and evolving CI/CD pipelines with Gitlab or Azure Data Ops.

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description Experian is looking for an experienced Senior Staff Engineer that, developing and delivering innovative direct to customer products on a cloud native platform developed using Java and the Spring Framework. You will be involved in projects using cutting-edge technologies as part of a senior software engineering team. You will be a key player in designing and implementing product features. This is a highly technical role requiring excellent coding skills. You will be responsible for developing core functionality and processing for a new powerful, enterprise level data platform built with Java and leveraging leading mainstream open-source technologies. Hands-On active collaboration as a core member of a software engineering team focused on building event driven services delivering highly secure, efficient and robust solutions in timeframe. You will report to director You will deliver highly available and scalable data streaming application functionality on an AWS cloud-based platform Diligently observe and maintain Standards for Regulatory Compliance and Information Security Deliver and maintain accurate, complete and current documentation Participate in full Agile cycle engagements, including meetings, iterative development, estimations, code reviews and design sessions Actively contribute to team architecture, engineering, and product discussions ensuring the team delivers best of breed software Work closely with the service quality engineering team to ensure that only thoroughly tested code makes it to production Own deliverables from design through production operationalization Qualifications 10+ years of software development experience building and testing applications following secure coding practices. Currently collaborating as a hands-on team member developing and supporting a significant commercial software project in Java with Spring Framework. Proven proficiency in developing server-side Java applications using mainstream frameworks, libraries, and tools including the Spring framework and AWS SDK. Experience developing web application using Spring Reactive libraries like WebFlux and Project Reactor as well as normal Spring Web. Experience with event driven architectures using pub/sub message brokers such as Kafka, Kinesis, and NATS.io. Knowledgeable and experienced with software and system patterns and their application in prior works. Current cloud technology experience AWS (Fargate, EC2, S3, RDS PostgreSQL, Lambda, API Gateway, Airflow). A strong proven proficiency in SQL and NoSQL based data access and management on PostgeSQL and MongoDB or AWS DocumentDB. Recent hands-on experience building and supporting commercial systems managing data and transactions including server-side development of Data Flow processes. Extensive experience gathering and assessing specifications and requirements. Extensive experience building systems for financial services or tightly regulated businesses. Security and privacy compliance (GPDR, CCPA, ISO 27001, PCI, HIPAA, etc.) experience. Experience with Continuous Integration/Continuous Delivery (CI/CD) process and practices (CodeCommit, CodeDeploy, CodePipeline/Harness/Jenkins/Github Actions, CLI, BitBucket/Git). Experience monitoring technologies including Splunk, Datadog, and Cloudwatch. Familiarity creating and using Docker/Kubernetes applications. Additional Information Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why. Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. Benefits Experian care for employee's work life balance, health, safety and wellbeing. In support of this endeavor, we offer the best family well-being benefits, Enhanced medical benefits and paid time off. Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here Show more Show less

GCP Data Engineer Remote Type: Fulltime Rate: Market Client -Telus Required Skills: ● 4+ years of industry experience in software development, data engineering, business intelligence, or related field with experience in manipulating, processing, and extracting value from datasets. ● Design, build and deploy internal applications to support our technology life cycle, collaboration and spaces, service delivery management, data and business intelligence among others. ● Building Modular code for multi usable pipeline or any kind of complex Ingestion Framework used to ease the job to load the data into Datalake or Data Warehouse from multiple sources. ● Work closely with analysts and business process owners to translate business requirements into technical solutions. ● Coding experience in scripting and languages (Python, SQL, PySpark). ● Expertise in Google Cloud Platform (GCP) technologies in the data warehousing space ( BigQuery , Google Composer, Airflow, CloudSQL, PostgreSQL, Oracle, GCP Workflows , Dataflow, Cloud Scheduler, Secret Manager, Batch, Cloud Logging, Cloud SDK, Google Cloud Storage, IAM, Vertex AI). ● Maintain highest levels of development practices including: technical design, solution development, systems configuration, test documentation/execution, issue identification and resolution, writing clean, modular and self-sustaining code, with repeatable quality and predictability. ● Understanding CI/CD Processes using Pulumi, Github, Cloud Build, Cloud SDK, Docker Show more Show less

Description GroundTruth is an advertising platform that turns real-world behavior into marketing that drives in-store visits and other real business results. We use observed real-world consumer behavior, including location and purchase data, to create targeted advertising campaigns across all screens, measure how consumers respond, and uncover unique insights to help optimize ongoing and future marketing efforts. With this focus on media, measurement, and insights, we provide marketers with tools to deliver media campaigns that drive measurable impact, such as in-store visits, sales, and more. Learn more at groundtruth.com. We believe that innovative technology starts with the best talent and have been ranked one of Ad Age’s Best Places to Work in 2021, 2022, 2023 & 2025! Learn more about the perks of joining our team here. You Will Create and maintain various ingestion pipelines for the GroundTruth platform. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies. Work with stakeholders, including the Product, Analytics and Client Services teams to assist with data-related technical issues and support their data infrastructure needs. Prepare detailed specifications and low-level design. Participate in code reviews. Test the product in controlled, real situations before going live. Maintain the application once it is live. Contribute ideas to improve the data platform. You Have Tech./B.E./M.Tech./MCA or equivalent in computer science 2-4 years of experience in Software Engineering Experience with AWS Stack used for Data engineering EC2, S3, EMR, ECS, Lambda, and Step functions Hands on experience with Python/Java for orchestration of data pipelines Experience in writing analytical queries using SQL Experience in Airflow Experience in Docker Proficient in Git How can you impress us? Knowledge of REST APIs. Any experience with big data technologies like Hadoop, MapReduce, and Pig is a plus Knowledge of shell scripting. Experience with BI tools like Looker. Experience with DB maintenance. Experience with Amazon Web Services and Docker. Configuration management and QA practices. Benefits At GroundTruth, we want our employees to be comfortable with their benefits so they can focus on doing the work they love. Parental leave- Maternity and Paternity Flexible Time Offs (Earned Leaves, Sick Leaves, Birthday leave, Bereavement leave & Company Holidays) In Office Daily Catered Breakfast, Lunch, Snacks and Beverages Health cover for any hospitalization. Covers both nuclear family and parents Tele-med for free doctor consultation, discounts on health checkups and medicines Wellness/Gym Reimbursement Pet Expense Reimbursement Childcare Expenses and reimbursements Employee referral program Education reimbursement program Skill development program Cell phone reimbursement (Mobile Subsidy program). Internet reimbursement/Postpaid cell phone bill/or both. Birthday treat reimbursement Employee Provident Fund Scheme offering different tax saving options such as Voluntary Provident Fund and employee and employer contribution up to 12% Basic Creche reimbursement Co-working space reimbursement National Pension System employer match Meal card for tax benefit Special benefits on salary account Show more Show less

Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Responsibilities As a data engineer, you will have the opportunity to apply your strong technical experience building highly reliable data products. You enjoy working in an agile environment. You are able to translate raw requirements into solid solutions. You are motivated by solving challenging problems, where creativity is as crucial as your ability to write code and test cases. On a typical day you will help our partner teams ingest data faster into our data lake, you’ll find ways to make our data products more efficient, or come up with ideas to help build self-serve data engineering within the company. Then you will move on to building micro-services, architecting, designing, and promoting self serve capabilities at scale to help Atlassian grow. Qualifications On your first day, we'll expect you to have: At least 3+ years of professional experience as a software engineer or data engineer A BS in Computer Science or equivalent experience Strong programming skills (some combination of Python, Java, and Scala) Experience writing SQL, structuring data, and data storage practices Experience with data modeling Knowledge of data warehousing concepts Experienced building data pipelines and micro services Experience with Spark, Airflow and other streaming technologies to process incredible volumes of streaming data A willingness to accept failure, learn and try again An open mind to try solutions that may seem impossible at first Experience in working on Amazon Web Services (in particular using EMR, Kinesis, RDS, S3, SQS and the like), and databricks. It's Preferred, But Not Technically Required, That You Have Experience building self-service tooling and platforms Built and designed Kappa architecture platforms A passion for building and running continuous integration pipelines. Built pipelines using Databricks and well versed with their API’s Contributed to open source projects (Ex: Operators in Airflow) Our Perks & Benefits Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more. About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh . Show more Show less

Primary Responsibilities: Design and develop applications and services running on Azure, with a strong emphasis on Azure Databricks, ensuring optimal performance, scalability, and security. Build and maintain data pipelines using Azure Databricks and other Azure data integration tools. Write, read, and debug Spark, Scala, and Python code to process and analyze large datasets. Write extensive query in SQL and Snowflake Implement security and access control measures and regularly audit Azure platform and infrastructure to ensure compliance. Create, understand, and validate design and estimated effort for given module/task, and be able to justify it. Possess solid troubleshooting skills and perform troubleshooting of issues in different technologies and environments. Implement and adhere to best engineering practices like design, unit testing, functional testing automation, continuous integration, and delivery. Maintain code quality by writing clean, maintainable, and testable code. Monitor performance and optimize resources to ensure cost-effectiveness and high availability. Define and document best practices and strategies regarding application deployment and infrastructure maintenance. Provide technical support and consultation for infrastructure questions. Help develop, manage, and monitor continuous integration and delivery systems. Take accountability and ownership of features and teamwork. Comply with the terms and conditions of the employment contract, company policies and procedures, and any directives. Required Qualifications: B.Tech/MCA (Minimum 16 years of formal education) Overall 7+ years of experience. Minimum of 3 years of experience in Azure (ADF), Databricks and DevOps. 5 years of experience in writing advanced leve l SQL. 2-3 years of experience in writing, reading, and debugging Spark, Scala, and Python code . 3 or more years of experience in architecting, designing, developing, and implementing cloud solutions on Azure. Proficiency in programming languages and scripting tools. Understanding of cloud data storage and database technologies such as SQL and NoSQL. Proven ability to collaborate with multidisciplinary teams of business analysts, developers, data scientists, and subject-matter experts. Familiarity with DevOps practices and tools, such as continuous integration and continuous deployment (CI/CD) and Teraform. Proven proactive approach to spotting problems, areas for improvement, and performance bottlenecks. Proven excellent communication, writing, and presentation skills. Experience in interacting with international customers to gather requirements and convert them into solutions using relevant skills. Preferred Qualifications: Knowledge of AI/ML or LLM (GenAI). Knowledge of US Healthcare domain and experience with healthcare data. Experience and skills with Snowflake.

Responsibilities: Ability to design and build Python-based code generation framework and runtime engine by reading Business Rules repository in order to. Requirements: Minimum 5 years of experience in build & deployment of Bigdata applications using SparkSQL, SparkStreaming in Python; Expertise on graph algorithms and advanced recursion techniques; Minimum 5 years of extensive experience in design, build and deployment of Python-based applications; Minimum 3 years of experience in the following: HIVE, YARN, Kafka, HBase, MongoDB; Hands-on experience in generating/parsing XML, JSON documents, and REST API request/responses; Bachelors degree in a quantitative field (such as Engineering, Computer Science, Statistics, Econometrics) and a minimum of 5 years of experience; Expertise in handling complex large-scale Big Data environments preferably (20Tb+); Hands-on experience writing complex SQL queries, exporting and importing large amounts of data using utilities.

About the Team Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on experienced engineers to help us further our 24x7, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers. About the Role The Data Tools mission is to build robust data platforms and establish policies that guarantee the analytics data is of high quality, easily accessible/cataloged, and compliant with financial and privacy regulations, fostering trust and confidence in our data-driven decision-making process. We are building the Data Tools team in India and you will have an opportunity to be part of a founding team with a greater opportunity for impact where you can help grow the team and shape the roadmap for the data platform at DoorDash. You will report directly to the Data Tools Engineering Manager. You're excited about this opportunity because you will… Work on building a data discovery platform, privacy frameworks, unified access control frameworks, and data quality platform to enable data builders at DoorDash to deliver high-quality and trustable data sets and metrics Help accelerate the adoption of the data discovery platform by building integrations across online, analytics platforms and promoting self-serve Come up with solutions for scaling data systems for various business needs Collaborate in a dynamic startup environment We're excited about you because… B.E./B.Tech., M.E./M.Tech, or Ph.D. in Computer Science or equivalent 6+ years of experience with CS fundamental concepts and experience with at least one of the programming languages of Scala, Java, and Python Prior technical experience in Big Data infrastructure & governance - you've built meaningful pieces of data infrastructure. Bonus if those were open-sourced technologies like DataHub, Spark, Airflow, Kafka, Flink Experience improving efficiency, scalability, and stability of data platforms Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees' happiness, healthiness, and overall well-being by providing comprehensive benefits and perks. Our Commitment to Diversity and Inclusion We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. If you need any accommodations, please inform your recruiting contact upon initial connection. About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees' happiness, healthiness, and overall well-being by providing comprehensive benefits and perks. Our Commitment to Diversity and Inclusion We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. If you need any accommodations, please inform your recruiting contact upon initial connection. We use Covey as part of our hiring and/or promotional process for jobs in certain locations. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144 To request a reasonable accommodation under applicable law or alternate selection process, please inform your recruiting contact upon initial connection. Show more Show less

This role is for one of the Weekday's clients Min Experience: 4 years Location: Ahmedabad JobType: full-time We are seeking a highly skilled Senior Database Administrator with 5-8 years of experience in data engineering and database management. The ideal candidate will have a strong foundation in data architecture, modeling, and pipeline orchestration. Hands-on experience with modern database technologies and exposure to generative AI tools in production environments will be a significant advantage. This role involves leading efforts to streamline data workflows, improve automation, and deliver high-impact insights across the organization. Requirements Key Responsibilities: Design, develop, and manage scalable and efficient data pipelines (ETL/ELT) across multiple database systems. Architect and maintain high-availability, secure, and scalable data storage solutions. Utilize generative AI tools to automate data workflows and enhance system capabilities. Collaborate with engineering, analytics, and data science teams to fulfill data requirements and optimize data delivery. Implement and monitor data quality standards, governance practices, and compliance protocols. Document data architectures, systems, and processes for transparency and maintainability. Apply data modeling best practices to support optimal storage and querying performance. Continuously research and integrate emerging technologies to advance the data infrastructure. Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or related field. 5-8 years of experience in database administration and data engineering for large-scale systems. Proven experience in designing and managing relational and non-relational databases. Mandatory Skills: SQL - Proficient in advanced queries, performance tuning, and database management. NoSQL - Experience with at least one NoSQL database such as MongoDB, Cassandra, or CosmosDB. Hands-on experience with at least one of the following cloud data warehouses: Snowflake, Redshift, BigQuery, or Microsoft Fabric. Cloud expertise - Strong experience with Azure and its data services. Working knowledge of Python for scripting and data processing (e.g., Pandas, PySpark). Experience with ETL tools such as Apache Airflow, Microsoft Fabric, Informatica, or Talend. Familiarity with generative AI tools and their integration into data pipelines. Preferred Skills & Competencies: Deep understanding of database performance, tuning, backup, recovery, and security. Strong knowledge of data governance, data quality management, and metadata handling. Experience with Git or other version control systems. Familiarity with AI/ML-driven data solutions is a plus. Excellent problem-solving skills and the ability to resolve complex database issues. Strong communication skills to collaborate with cross-functional teams and stakeholders. Demonstrated ability to manage projects and mentor junior team members. Passion for staying updated with the latest trends and best practices in database and data engineering technologies. Show more Show less

Roles and Responsibilities: Data Pipeline Development: Design, develop, and maintain scalable data pipelines to support ETL (Extract, Transform, Load) processes using tools like Apache Airflow, AWS Glue, or similar. Database Management: Design, optimize, and manage relational and NoSQL databases (such as MySQL, PostgreSQL, MongoDB, or Cassandra) to ensure high performance and scalability. SQL Development: Write advanced SQL queries, stored procedures, and functions to extract, transform, and analyze large datasets efficiently. Cloud Integration: Implement and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud, utilizing services like Redshift, BigQuery, or Snowflake. Data Warehousing: Contribute to the design and maintenance of data warehouses and data lakes to support analytics and BI requirements. Programming and Automation: Develop scripts and applications in Python or other programming languages to automate data processing tasks. Data Governance: Implement data quality checks, monitoring, and governance policies to ensure data accuracy, consistency, and security. Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data needs and translate them into technical solutions. Performance Optimization: Identify and resolve performance bottlenecks in data systems and optimize data storage and retrieval. Documentation: Maintain comprehensive documentation for data processes, pipelines, and infrastructure. Stay Current: Keep up-to-date with the latest trends and advancements in data engineering, big data technologies, and cloud services. Required Skills and Qualifications: Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field. Technical Skills: Proficiency in SQL and relational databases (PostgreSQL, MySQL, etc.). Experience with NoSQL databases (MongoDB, Cassandra, etc.). Strong programming skills in Python; familiarity with Java or Scala is a plus. Experience with data pipeline tools (Apache Airflow, Luigi, or similar). Expertise in cloud platforms (AWS, Azure, or Google Cloud) and data services (Redshift, Big Query, Snowflake). Knowledge of big data tools like Apache Spark, Hadoop, or Kafka is a plus. Data Modeling: Experience in designing and maintaining data models for relational and non-relational databases. Analytical Skills: Strong analytical and problem-solving abilities with a focus on performance optimization and scalability. Soft Skills: Excellent verbal and written communication skills to convey technical concepts to non-technical stakeholders. Ability to work collaboratively in cross-functional teams. Certifications (Preferred): AWS Certified Data Analytics, Google Professional Data Engineer, or similar. Mindset: Eagerness to learn new technologies and adapt quickly in a fast-paced environment. Show more Show less

As a Software Developer you will work in a constantly evolving environment, due to technological advances and the strategic direction of the organization you work for. You will create, maintain, audit, and improve systems to meet particular needs, often as advised by a systems analyst or architect, testing both hard and software systems to diagnose and resolve system faults. The role also covers writing diagnostic programs and designing and writing code for operating systems and software to ensure efficiency. When required, you will make recommendations for future developments Benefits of Joining Us Challenging Projects : Work on cutting-edge projects and solve complex technical problems. Career Growth : Advance your career quickly and take on leadership roles. Mentorship : Learn from experienced mentors and industry experts. Global Opportunities : Work with clients from around the world and gain international experience. Competitive Compensation : Receive attractive compensation packages and benefits. If you're passionate about technology and want to work on challenging projects with a talented team, becoming an Infosys Power Programmer could be a great career choice. Mandatory Skills AWS Glue, AWS Redshift/Spectrum, S3, API Gateway, Athena, Step and Lambda functions Experience in Extract Transform Load (ETL) and Extract Load & Transform (ELT) data integration pattern. Experience in designing and building data pipelines. Development experience in one or more object-oriented programming languages, preferably Python Job Specs 5+ years of in depth hands on experience of developing, testing, deployment and debugging of Spark Jobs using Scala in Hadoop Platform In depth knowledge of Spark Core, working with RDDs, Spark SQL In depth knowledge on Spark Optimization Techniques and Best practices Good Knowledge of Scala Functional Programming: Try, Option, Future, Collections Good Knowledge of Scala OOPS: Classes, Traits and Objects (Singleton and Companion), Case Classes Good Understanding of Scala Language Features: Type System, Implicit/Givens Hands on experience of working in Hadoop Environment (HDFS/Hive), AWS S3, EMR Python programming skills Working experience on Workflow Orchestration tools like Airflow, Oozie Working with API calls in Scala Understanding and exposure to file formats such as Apache AVRO, Parquet, JSON Good to have knowledge of Protocol Buffers and Geospatial data analytics. Writing Test cases using frameworks such as scalatest. Good Knowledge of Build Tools such as: Gradle & SBT in depth Experience on using GIT, resolving conflicts, working with branches. Good to have worked on some workflow systems as Airflow Strong programming skills using data structures and algorithms. Excellent analytical skills Good communication skills Qualification 7-10 Yrs in the industry BE/B.tech CS or equivalent Show more Show less

Company Description ThreatXIntel is a startup cyber security company dedicated to providing customized, affordable solutions to protect businesses and organizations from cyber threats. Our services include cloud security, web and mobile security testing, cloud security assessment, and DevSecOps. We take a proactive approach to security, continuously monitoring and testing our clients' digital environments to identify vulnerabilities before they can be exploited. Role Description We are looking for a freelance Data Engineer with strong experience in PySpark and AWS data services, particularly S3 and Redshift . The ideal candidate will also have some familiarity with integrating or handling data from Salesforce . This role focuses on building scalable data pipelines, transforming large datasets, and enabling efficient data analytics and reporting. Key Responsibilities: Develop and optimize ETL/ELT data pipelines using PySpark for large-scale data processing. Manage data ingestion, storage, and transformation across AWS S3 and Redshift . Design data flows and schemas to support reporting, analytics, and business intelligence needs. Perform incremental loads, partitioning, and performance tuning in distributed environments. Extract and integrate relevant datasets from Salesforce for downstream processing. Ensure data quality, consistency, and availability for analytics teams. Collaborate with data analysts, platform engineers, and business stakeholders. Required Skills: Strong hands-on experience with PySpark for large-scale distributed data processing. Proven track record working with AWS S3 (data lake) and Amazon Redshift (data warehouse). Ability to write complex SQL queries for transformation and reporting. Basic understanding or experience integrating data from Salesforce (APIs or exports). Experience with performance optimization, partitioning strategies, and efficient schema design. Knowledge of version control and collaborative development tools (e.g., Git). Nice to Have: Experience with AWS Glue or Lambda for orchestration. Familiarity with Salesforce objects, SOQL, or ETL tools like Talend, Informatica, or Airflow. Understanding of data governance and security best practices in cloud environments. Show more Show less

Job Title: Data Engineer – AWS Full Stack Location: India (Remote or Hybrid) Contract Type: Full-time, 1-Year Contract Experience Required: Minimum 5 years Start Date: Immediate Compensation: Competitive (Based on experience) About the Role We are seeking a highly skilled Data Engineer with deep expertise in the AWS ecosystem and full-stack data engineering . The ideal candidate will be responsible for designing, developing, and maintaining robust data pipelines and analytics platforms that support critical business insights and decision-making. This is a 1-year contract role ideal for professionals who have experience across data ingestion, transformation, cloud infrastructure, and data operations. Key Responsibilities Design and build end-to-end data pipelines using AWS services (Glue, Lambda, S3, Athena, Redshift, EMR, etc.). Develop and manage ETL/ELT processes , ensuring data quality, scalability, and maintainability. Collaborate with product, analytics, and engineering teams to deliver data models, APIs, and real-time data solutions . Implement best practices for data governance, lineage, monitoring, and access control . Automate data workflows using tools like Airflow, Step Functions , or custom scripts. Create and maintain infrastructure as code (IaC) using CloudFormation or Terraform for AWS data components. Optimize data warehouse and lakehouse architectures for performance and cost. Required Skills & Qualifications 5+ years of experience in data engineering, including cloud-native data development. Strong expertise in AWS data services : Glue, S3, Lambda, Redshift, Athena, Kinesis, EMR, etc. Proficiency in SQL, Python, and Spark for data manipulation and transformation. Experience with DevOps tools (CI/CD, Git, Docker) and infrastructure automation. Knowledge of data modeling , schema design, and performance tuning for large-scale datasets. Ability to work independently in a contract environment , managing priorities and deadlines. Preferred Qualifications Familiarity with streaming data architectures using Kafka/Kinesis. Experience working in regulated or large-scale enterprise environments . Exposure to BI tools (e.g., QuickSight, Tableau, Power BI) and API integration for downstream consumption. Show more Show less

Data is at the core of the Aladdin platform, and increasingly, our ability to consume, store, analyze, and gain insight from data is a keycomponentof what differentiates us. As part of Aladdin Studio, The Aladdin Data Cloud (ADC) Engineering teamis responsible forbuilding andmaintainingdata-as-a-service solution for all the data management and transformation needs. We engineer high performance data pipelines, provide a fabric to discover and consume data, and continually evolve our data surface capabilities. As aData engineer in theADCEngineering team,you will: - Work alongside our engineers to help design and build scalable data pipelines while evolving the data surface. Help prove out anddeliverCloud Native Infrastructure and tooling to support scalabledata cloud. Have fun as part of anamazingteam. Specific Responsibilities: Leading and working as part of a multi-disciplinary squad toestablishour next generation of data pipelines and tools. Be involved frominceptionof projects, understanding requirements, designing&developing solutions,and incorporating them into the designs of our platforms. Mentor team members on technology andstandard processes. Maintainexcellent knowledge of the technical landscapefor data & cloud tooling Assistinsolvingissues, support the operation of production software. Designsolutions and document it. Desirable Skills 8+years of industry experience in data engineering area. Passionfor engineeringandoptimizing data sets, data pipelines and architecture . Ability to build processes that support data transformation, workload management, data structures,lineage,and metadata. Knowledge of SQL and performance tuning.Experience with Snowflake is preferred. Good understandingoflanguages such as Python/Java Understandingofsoftware deployment and orchestration technologies such asairflowetc. Experience withdbtishelpful. Working knowledge of building and deploying distributed systems Experience in creating and evolving CI/CD pipelines with GitLab orAzure Dev Ops . Experience in handling multi-disciplinaryteamand mentoring them.

Role Summary Pfizer’s purpose is to deliver breakthroughs that change patients’ lives. Research and Development is at the heart of fulfilling Pfizer’s purpose as we work to translate advanced science and technologies into the therapies and vaccines that matter most. Whether you are in the discovery sciences, ensuring drug safety and efficacy or supporting clinical trials, you will apply cutting edge design and process development capabilities to accelerate and bring the best in class medicines to patients around the world. Pfizer is seeking a highly skilled and motivated AI Engineer to join our advanced technology team. The successful candidate will be responsible for developing, implementing, and optimizing artificial intelligence models and algorithms to drive innovation and efficiency in our Data Analytics and Supply Chain solutions. This role demands a collaborative mindset, a passion for cutting-edge technology, and a commitment to improving patient outcomes. Role Responsibilities Lead data modeling and engineering efforts within advanced data platforms teams to achieve digital outcomes. Provides guidance and may lead/co-lead moderately complex projects. Oversee the development and execution of test plans, creation of test scripts, and thorough data validation processes. Lead the architecture, design, and implementation of Cloud Data Lake, Data Warehouse, Data Marts, and Data APIs. Lead the development of complex data products that benefit PGS and ensure reusability across the enterprise. Collaborate effectively with contractors to deliver technical enhancements. Oversee the development of automated systems for building, testing, monitoring, and deploying ETL data pipelines within a continuous integration environment. Collaborate with backend engineering teams to analyze data, enhancing its quality and consistency. Conduct root cause analysis and address production data issues. Lead the design, develop, and implement AI models and algorithms to solve sophisticated data analytics and supply chain initiatives. Stay abreast of the latest advancements in AI and machine learning technologies and apply them to Pfizer's projects. Provide technical expertise and guidance to team members and stakeholders on AI-related initiatives. Document and present findings, methodologies, and project outcomes to various stakeholders. Integrate and collaborate with different technical teams across Digital to drive overall implementation and delivery. Ability to work with large and complex datasets, including data cleaning, preprocessing, and feature selection. Basic Qualifications A bachelor's or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related discipline. Over 4 years of experience as a Data Engineer, Data Architect, or in Data Warehousing, Data Modeling, and Data Transformations. Over 2 years of experience in AI, machine learning, and large language models (LLMs) development and deployment. Proven track record of successfully implementing AI solutions in a healthcare or pharmaceutical setting is preferred. Strong understanding of data structures, algorithms, and software design principles Programming Languages: Proficiency in Python, SQL, and familiarity with Java or Scala AI and Automation: Knowledge of AI-driven tools for data pipeline automation, such as Apache Airflow or Prefect. Ability to use GenAI or Agents to augment data engineering practices Preferred Qualifications Data Warehousing: Experience with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake. ETL Tools: Knowledge of ETL tools like Apache NiFi, Talend, or Informatica. Big Data Technologies: Familiarity with Hadoop, Spark, and Kafka for big data processing. Cloud Platforms: Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP). Containerization: Understanding of Docker and Kubernetes for containerization and orchestration. Data Integration: Skills in integrating data from various sources, including APIs, databases, and external files. Data Modeling: Understanding of data modeling and database design principles, including graph technologies like Neo4j or Amazon Neptune. Structured Data: Proficiency in handling structured data from relational databases, data warehouses, and spreadsheets. Unstructured Data: Experience with unstructured data sources such as text, images, and log files, and tools like Apache Solr or Elasticsearch. Data Excellence: Familiarity with data excellence concepts, including data governance, data quality management, and data stewardship. Non-standard Work Schedule, Travel Or Environment Requirements Occasionally travel required Work Location Assignment: Hybrid The annual base salary for this position ranges from $96,300.00 to $160,500.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 12.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. Relocation assistance may be available based on business needs and/or eligibility. Sunshine Act Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. EEO & Employment Eligibility Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States. Information & Business Tech Show more Show less

Job Summary: We are seeking a highly skilled and innovative Data Scientist to join our team and drive data-centric initiatives by leveraging AI/ML models , Big Data technologies , and cloud platforms like AWS . The ideal candidate will be proficient in Python , experienced in designing end-to-end machine learning pipelines, and comfortable working with large-scale data systems. Key Responsibilities: Design, develop, and deploy machine learning models and AI-based solutions for business problems. Build robust ETL pipelines to process structured and unstructured data using tools like PySpark , Airflow , or Glue . Work with AWS cloud services (e.g., S3, Lambda, SageMaker, Redshift, EMR) to build scalable data science solutions. Perform exploratory data analysis (EDA) and statistical modeling to uncover actionable insights. Collaborate with data engineers, product managers, and stakeholders to identify use cases and deliver impactful data-driven solutions. Optimize model performance and ensure model explainability, fairness, and reproducibility. Maintain and improve existing data science solutions through MLOps practices (e.g., model monitoring, retraining, CI/CD for ML). Required Skills and Qualifications: Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, or related field. 3+ years of experience in data science or machine learning roles. Strong programming skills in Python and experience with libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch . Show more Show less

We are seeking a highly skilled Product Data Engineer with expertise in building, maintaining, and optimizing data pipelines using Python scripting. The ideal candidate will have experience working in a Linux environment, managing large-scale data ingestion, processing files in S3, and balancing disk space and warehouse storage efficiently. This role will be responsible for ensuring seamless data movement across systems while maintaining performance, scalability, and reliability. Key Responsibilities: ETL Pipeline Development: Design, develop, and maintain efficient ETL workflows using Python to extract, transform, and load data into structured data warehouses. Data Pipeline Optimization: Monitor and optimize data pipeline performance, ensuring scalability and reliability in handling large data volumes. Linux Server Management: Work in a Linux-based environment, executing command-line operations, managing processes, and troubleshooting system performance issues. File Handling & Storage Management: Efficiently manage data files in Amazon S3, ensuring proper storage organization, retrieval, and archiving of data. Disk Space & Warehouse Balancing: Proactively monitor and manage disk space usage, preventing storage bottlenecks and ensuring warehouse efficiency. Error Handling & Logging: Implement robust error-handling mechanisms and logging systems to monitor data pipeline health. Automation & Scheduling: Automate ETL processes using cron jobs, Airflow, or other workflow orchestration tools. Data Quality & Validation: Ensure data integrity and consistency by implementing validation checks and reconciliation processes. Security & Compliance: Follow best practices in data security, access control, and compliance while handling sensitive data. Collaboration with Teams: Work closely with data engineers, analysts, and product teams to align data processing with business needs. Skills Required: Proficiency in Python: Strong hands-on experience in writing Python scripts for ETL processes. Linux Expertise: Experience working with Linux servers, command-line operations, and system performance tuning. Cloud Storage Management: Hands-on experience with Amazon S3, including handling file storage, retrieval, and lifecycle policies. Data Pipeline Management: Experience with ETL frameworks, data pipeline automation, and workflow scheduling (e.g., Apache Airflow, Luigi, or Prefect). SQL & Database Handling: Strong SQL skills for data extraction, transformation, and loading into relational databases and data warehouses. Disk Space & Storage Optimization: Ability to manage disk space efficiently, balancing usage across different systems. Error Handling & Debugging: Strong problem-solving skills to troubleshoot ETL failures, debug logs, and resolve data inconsistencies. Nice to Have: Experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery). Knowledge of message queues (Kafka, RabbitMQ) for data streaming. Familiarity with containerization tools (Docker, Kubernetes) for deployment. Exposure to infrastructure automation tools (Terraform, Ansible). Qualifications: Bachelor’s degree in Computer Science, Data Engineering, or a related field. 4+ years of experience in ETL development, data pipeline management, or backend data engineering. Strong analytical mindset and ability to handle large-scale data processing efficiently. Ability to work independently in a fast-paced, product-driven environment. Show more Show less

Role Overview: We are seeking an experienced DevOps Engineer with a strong background in managing AI-related operations and application development processes. The ideal candidate will have a deep understanding of DevOps practices, infrastructure automation, and the deployment and monitoring of AI/ML models in production environments. Key Responsibilities: Set up and maintain CI/CD pipelines (GitHub Actions, GitLab CI/CD, Jenkins) Infra provisioning with Terraform, CloudFormation, or Ansible Manage ML pipelines using Kubeflow, MLflow, Airflow, or Metaflow Deploy and manage containerized services using Docker and Kubernetes (EKS preferred) Design scalable, reliable systems on AWS (Auto Scaling, ELB, ECS/EKS, RDS, S3, CloudFront, etc.) Set up monitoring/logging with Prometheus, Grafana, CloudWatch, ELK, or DataDog Collaborate with data and backend teams for model deployment and lifecycle management Implement security best practices and drive incident response + RCA when needed Stay updated on new DevOps/MLOps tools to improve system efficiency Required Qualifications: 3–5+ years in DevOps or similar role Strong AWS experience — especially with scaling, HA design, and core services (EC2, EKS, RDS, S3) Good experience with CI/CD tools and Infrastructure as Code (Terraform, CloudFormation, Ansible) Hands-on with Docker, Kubernetes, and managing containerized workloads Experience deploying ML models in production environments Familiarity with monitoring and alerting tools (Prometheus, Grafana, ELK, etc.) Cloud and container security awareness Nice to Have: Experience with MLOps platforms (Kubeflow, MLflow, SageMaker, Vertex AI, Metaflow) Scripting in Python or Bash Experience with config management tools like Ansible, Chef, or Puppet Understanding of VPC, IAM, cost optimization, and fault-tolerant architecture About the Company: Griphic is founded by IIT Delhi engineers. Our vision is to enrich lives through technological innovation. We combine cutting-edge AI with hyper-realistic virtual experiences to solve problems and bring disruption in the industry. We have a dynamic team with engineers from IIT Delhi, AI/ML engineers, VR developers, and many more. Our startup is backed by the world’s leading design documentation firm, SKETS Studio, which has a strength of 700+ people and specializes in BIM, architecture, VR, and 3D visualization. Interested candidates should submit their resumes at jobs@griphic.com along with a brief cover letter and any relevant project examples or GitHub links. Show more Show less

Work Experience : 3+ years Salary: 21 LPA Location: Bengaluru Title : MLops Engineer Team Charter: The team in India comes with multi-disciplinary skillset, including but not limited to the following areas: Develop models and algorithms using Deep Learning and Computer Vision on the captured data to provide meaningful analysis to our customers. Some of the projects include – object detection, OCR, barcode scanning, stereovision, SLAM, 3D-reconstruction, action recognition etc. Develop integrated embedded systems for our drones – including embedded system platform development, camera and sensor integration, flight controller and motor control system development, etc. Architect and develop full stack software to interface between our solution and customer database and access – including database development, API development, UI/UX, storage, security and processing for data acquired by the drone. Integration and testing of various off the shelf sensors and other modules with drone and related software. Design algorithms related to autonomy and flight controls. Responsibilities: As a Machine Learning Ops (MLOps) engineer, you will be responsible for building and maintaining the next generation of Vimaan’s ML Platform and Infrastructure. MLOps will have a major contribution in making CV & ML offerings scalable across the company products. We are building all these data & model pipelines to scale Vimaan operations and MLOps Engineer will play a key role in enabling that. You will lead initiatives geared towards making the Computer Vision Engineers at Vimaan more productive. You will setup the infrastructure that powers the ML teams, thus simplifying the development and deployment cycles of ML models. You will help establish best practices for the ML pipeline and partner with other infrastructure ops teams to help champion them across the company. Build and maintain data pipelines - data ingestion, filtering, generating pre-populated annotations, etc. Build and maintain model pipelines - model monitoring, automated triggering of model (re)training, auto-deployment of models to producti on servers and edge devices. Own the cloud stack which comprises all ML resources. Establish standards and practices around MLOps, including governance, compliance, and data security. Collaborate on managing ML infrastructure costs. Qualifications: Deep quantitative/programming background with degree (Bachelors, Masters or Ph.D.) in a highly analytical discipline, like Statistics, Electrical,Electronics, Computer Science, Mathematics, Operations Research, etc. A minimum of 3 years of experience in managing machine learning projects end-to-end focused on MLOps. Experience with building RESTful APIs for monitoring build & production systems using automated monitoring of models and corresponding alarm tools. Experience with data versioning tools such as Data Version Control (DVC). Build and maintain data pipelines by using tools like Dagster, Airflow etc. Experience with containerizing and deploying ML models. Hands-on experience with autoML tools, experiment tracking, model management, version tracking & model training (MLflow, W&B, Neptune etc.), model hyperparameter optimization, model evaluation, and visualization (Tensorboard). Sound knowledge and experience with atleast one DL frameworks such as PyTorch, TensorFlow, Keras. Experience with container technologies (Docker, Kubernetes etc). Experience with cloud services. Working knowledge of SQL based databases. Hands on experience with Python scientific computing stack such as numpy, scipy, scikit-learn Familiarity with Linux and git. Detail oriented design, code debugging and problem-solving skills. Effective communication skills: discussing with peers and driving logic driven conclusions. Ability to perspicuously communicate complex technical/architectural problems and propose solutions for the same. How to stand out Prior experience in deploying ML & DL solutions as services Experience with multiple cloud services. Ability to collaborate effectively across functions in a fast-paced environment. Experience with technical documentation and presentation for effective dissemination of work. Engineering experience in distributed systems and data infrastructure. Show more Show less

Education: Bachelor’s or master’s in computer science, Software Engineering, or a related field (or equivalent practical experience). Hands-On ML/AI Experience: Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. Programming & Frameworks: Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). Security & Compliance: Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. DevOps Knowledge: Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Collaborative Mindset: Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Role Overview Collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. Lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities LLM Pipeline Ownership: Set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. Data Governance & Security: Assist our IT department to implement role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. Infrastructure & Tooling: Oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. Software Development: Build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). Integration & Automation: Collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. Best Practices & Documentation: Define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. Team Support & Training: Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model “hallucinations.” Performance Monitoring: Track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Job Types: Full-time, Permanent Pay: ₹80,000.00 - ₹90,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person Application Deadline: 30/06/2025 Expected Start Date: 30/06/2025

Responsibilities Actively participate in chapter ceremony meetings and contribute to project planning and estimation. Coordinate work with product managers, data owners, platform teams, and other stakeholders throughout the SDLC cycle. Use Airflow, Python, Snowflake, dbt, and related technologies to enhance and maintain EDP acquisition, ingestion, processing, orchestration and DQ frameworks. Adopt new tools and technologies to enhance framework capabilities. Build and conduct end-to-end tests to ensure production operations run successfully after every release cycle. Document and present accomplishments and challenges to internal and external stakeholders. Demonstrate deep understanding of modern data engineering tools and best practices. Design and build solutions which are performant, consistent, and scalable. Contribute to design decisions for complex systems. Provide L2 / L3 support for technical and/or operational issues. Qualifications At least 5+ years experience as a data engineer Expertise with SQL, stored procedures, UDFs Advanced level Python programming or Advanced Core Java programming. Experience with Snowflake or similar cloud native databases Experience with orchestration tools, especially Airflow Experience with declarative transformation tools like dbt Experience in Azure services, especially ADLS (or equivalent) Exposure to real time streaming platforms and message brokers (e.g., Snowpipe Streaming, Kafka) Experience with Agile development concepts and related tools (ADO, Aha) Experience conducting root cause analysis and solve issues Experience with performance tuning Excellent written and verbal communication skills Ability to operate in a matrixed organization and fast-paced environment Strong interpersonal skills with a can-do attitude under challenging circumstances Bachelors degree in computer science is strongly preferred

We’re Hiring: MLOps Engineer (Azure) harshita.panchariya@tecblic.com Location: Ahmedabad, Gujarat Experience: 3–5 Years Employment Type : Full-Time * An immediate joiner will be preferred. Job Summary: We are seeking a skilled and proactive MLOps/DataOps Engineer with strong experience in the Azure ecosystem to join our team. You will be responsible for streamlining and automating machine learning and data pipelines, supporting scalable deployment of AI/ML models, and ensuring robust monitoring, governance, and CI/CD practices across the data and ML lifecycle. Key Responsibilities MLOps : Design and implement CI/CD pipelines for machine learning workflows using Azure DevOps, GitHub Actions, or Jenkins. Automate model training, validation, deployment, and monitoring using tools such as Azure ML, MLflow, or KubeFlow. Manage model versioning, performance tracking, and rollback strategies. Integrate machine learning models with APIs or web services using Azure Functions, Azure Kubernetes Service (AKS), or Azure App Services. DataOps Design, build, and maintain scalable data ingestion, transformation, and orchestration pipelines using Azure Data Factory, Synapse Pipelines, or Apache Airflow. Ensure data quality, lineage, and governance using Azure Purview or other metadata management tools. Monitor and optimize data workflows for performance and cost efficiency. Support batch and real-time data processing using Azure Stream Analytics, Event Hubs, Databricks, or Kafka. DevOps & Infrastructure Provision and manage infrastructure using Infrastructure-as-Code tools such as Terraform, ARM Templates, or Bicep. Set up and manage compute environments (VMs, AKS, AML Compute), storage (Blob, Data Lake Gen2), and networking in Azure. Implement observability using Azure Monitor, Log Analytics, Application Insights, and Skills : Strong hands-on experience with Azure Machine Learning, Azure Data Factory, Azure DevOps, and Azure Storage solutions. Proficiency in Python, Bash, and scripting for automation. Experience with Docker, Kubernetes, and containerized deployments in Azure. Good understanding of CI/CD principles, testing strategies, and ML lifecycle management. Familiarity with monitoring, logging, and alerting in cloud environments. Knowledge of data modeling, data warehousing, and SQL. Preferred Qualifications Azure Certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate, or Azure DevOps Engineer Expert). Experience with Databricks, Delta Lake, or Apache Spark on Azure. Exposure to security best practices in ML and data environments (e.g., identity management, network security). Soft Skills Strong problem-solving and communication skills. Ability to work independently and collaboratively with data scientists, ML engineers, and platform teams. Passion for automation, optimization, and driving operational excellence. harshita.panchariya@tecblic.com Show more Show less

Key Responsibilities: Data Pipeline Development : Assist in the design and implementation of data pipelines to extract, transform, and load (ETL) data from various sources into data warehouses or databases. Data Quality Assurance : Monitor and ensure the quality and integrity of data throughout the data lifecycle, identifying and resolving any data discrepancies or issues. Collaboration & Analysis : Work closely with data analysts, data scientists, and other stakeholders to understand data requirements and deliver solutions that meet business needs as well as perform analyses aligned to anchor domain. Documentation : Maintain clear and comprehensive documentation of data processes, pipeline architectures, and data models for reference and training purposes. Performance Optimization : Help optimize data processing workflows and improve the efficiency of existing data pipelines. Support Data Infrastructure : Assist in the maintenance and monitoring of data infrastructure, ensuring systems are running smoothly and efficiently. Learning and Development : Stay updated on industry trends and best practices in data engineering, actively seeking opportunities to learn and grow in the field. Qualifications Education: Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field preferred; relevant coursework or certifications in data engineering or programming is a plus. Technical Skills: Familiarity with programming languages such as Python or JavaScript; knowledge of SQL and experience with databases (e.g., Snowflake, MySQL, or PostgreSQL) is preferred. Data Tools: Exposure to data processing frameworks and tools (e.g. PBS/Torque, Slurm, or Airflow) is a plus. Analytical Skills: Strong analytical and problem-solving skills, with a keen attention to detail. Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical information clearly to non-technical stakeholders. Team Player: Ability to work collaboratively in a team environment and contribute to group projects. Adaptability: Willingness to learn new technologies and adapt to changing priorities in a fast-paced environment.

About Job: About Client Our Client is a global IT services company headquartered in Southborough, Massachusetts, USA. Founded in 1996, with a revenue of $1.8B, with 35,000+ associates worldwide, specializes in digital engineering, and IT services company helping clients modernize their technology infrastructure, adopt cloud and AI solutions, and accelerate innovation. It partners with major firms in banking, healthcare, telecom, and media. Our Client is known for combining deep industry expertise with agile development practices, enabling scalable and cost-effective digital transformation. The company operates in over 50 locations across more than 25 countries, has delivery centers in Asia, Europe, and North America and is backed by Baring Private Equity Asia. Job Title : AWS Data Engineer Key Skills : AWS, Data Engineer, Python , ETL, Snowflake, Apache Airflow. Locations : PAN INDIA Experience : 8- 10 years Education Qualification : Any Graduation Work Mode : Hybrid Employment Type : Contract to Hire Notice Period : Immediate - 10 Days. Job Description: 8 to 10 years of experience in data engineering roles with a focus on building scalable data solutions. Proficiency in Python for ETL, data manipulation, and scripting. Hands-on experience with Snowflake or equivalent cloud-based data warehouses. Strong knowledge of orchestration tools such as Apache Airflow or similar. Expertise in implementing and managing messaging queues like Kafka , AWS SQS , or similar. Demonstrated ability to build and optimize data pipelines at scale, processing terabytes of data. Experience in data modeling, data warehousing, and database design. Proficiency in working with cloud platforms like AWS, Azure, or GCP. Strong understanding of CI/CD pipelines for data engineering workflows. Experience working in an Agile development environment , collaborating with cross-functional teams. Show more Show less