365 Athena Jobs - Page 9

Meeting with managers for company’s Big Data needs Developing big data solutions on AWS using Apache Spark, Databricks, Delta Tables, EMR, Athena, Glue, Hadoop Loading disparate data sets & conducting pre-processing services using Athena, Glue, Spark Required Candidate profile Proficient with Python & PySpark Extensive experience with Delta Tables, JSON, Parquet file format AWS data analytics services like Athena, Glue, Redshift, EMR Knowledge of NoSQL and RDBMS databases.

Overview Annalect is currently seeking a data engineer to join our technology team. In this role you will build Annalect products which sit atop cloud-based data infrastructure. We are looking for people who have a shared passion for technology, design & development, data, and fusing these disciplines together to build cool things. In this role, you will work on one or more software and data products in the Annalect Engineering Team. You will participate in technical architecture, design, and development of software products as well as research and evaluation of new technical solutions. Responsibilities Design, build, test and deploy scalable and reusable systems that handle large amounts of data. Collaborate with product owners and data scientists to build new data products. Ensure data quality and reliability Qualifications Experience designing and managing data flows. Experience designing systems and APIs to integrate data into applications. 4+ years of Linux, Bash, Python, and SQL experience 2+ years using Spark and other frameworks to process large volumes of data. 2+ years using Parquet, ORC, or other columnar file formats. 2+ years using AWS cloud services, esp. services that are used for data processing e.g. Glue, Dataflow, Data Factory, EMR, Dataproc, HDInsights , Athena, Redshift, BigQuery etc. Passion for Technology: Excitement for new technology, bleeding edge applications, and a positive attitude towards solving real world challenges

Job Title: Senior Data Associate - Cloud Data Engineering Experience: 7+ Years Employment Type: Full-Time Industry: Information Technology / Data Engineering / Cloud Platforms Job Summary: We are seeking a highly skilled and experienced Senior Data Associate to join our data engineering team. The ideal candidate will have a strong background in cloud data platforms, big data processing, and enterprise data systems, with hands-on experience across both AWS and Azure ecosystems. This role involves building and optimizing data pipelines, managing large-scale data lakes and warehouses, and enabling advanced analytics and reporting. Key Responsibilities: Design, develop, and maintain scalable data pipelines using AWS Glue, PySpark, and Azure Data Factory. Work with AWS Redshift, Athena, Azure Synapse, and Databricks to support data warehousing and analytics solutions. Integrate and manage data across MongoDB, Oracle, and cloud-native storage like Azure Data Lake and S3. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality datasets. Implement data quality checks, monitoring, and governance practices. Optimize data workflows for performance, scalability, and cost-efficiency. Support data migration and modernization initiatives across cloud platforms. Document data flows, architecture, and technical specifications. Required Skills & Qualifications: 7+ years of experience in data engineering, data integration, or related roles. Strong hands-on experience with: AWS Redshift, Athena, Glue, S3 Azure Data Lake, Synapse Analytics, Databricks PySpark for distributed data processing MongoDB and Oracle databases Proficiency in SQL, Python, and data modeling. Experience with ETL/ELT design and implementation. Familiarity with data governance, security, and compliance standards. Strong problem-solving and communication skills. Preferred Qualifications: Certifications in AWS (e.g., Data Analytics Specialty) or Azure (e.g., Azure Data Engineer Associate). Experience with CI/CD pipelines and DevOps for data workflows. Knowledge of data cataloging tools (e.g., AWS Glue Data Catalog, Azure Purview). Exposure to real-time data processing and streaming technologies. Required Skills Azure,AWS REDSHIFT,Athena,Azure Data Lake

The resource should have a strong background in working with cloud platforms, APIs, and data processing. Experience with tools like AWS Glue, Athena, and Databricks will be highly beneficial. AWS Glue Jobs: The QE should have familiarity with AWS Glue jobs for ETL processes. We expect them to validate the successful execution of around Glue jobs, ensuring that transformations and data ingestion tasks are working smoothly without errors. Athena Querying: Experience with querying data using AWS Athena is a must, as the QE will be required to validate queries across multiple datasets. We expect the resource to run and validate Athena queries for data accuracy and integrity. Databricks Testing: The candidate should also have experience with Databricks, particularly in validating data pipelines and transformations within the Databricks environment. The QE will need to test Databricks notebooks or jobs, ensuring data accuracy in the Bronze, Silver, and Gold layers. Boomi integrations

Job Title: Data Engineer II (Python, SQL) Experience: 3 to 6 years Location: Bangalore, Karnataka (Work from office, 5 days a week) Role: Data Engineer II (Python, SQL) As a Data Engineer II, you will work on designing, building, and maintaining scalable data pipelines. Youll collaborate across data analytics, marketing, data science, and product teams to drive insights and AI/ML integration using robust and efficient data infrastructure. Key Responsibilities: Design, develop and maintain end-to-end data pipelines (ETL/ELT). Ingest, clean, transform, and curate data for analytics and ML usage. Work with orchestration tools like Airflow to schedule and manage workflows. Implement data extraction using batch, CDC, and real-time tools (e.g., Debezium, Kafka Connect). Build data models and enable real-time and batch processing using Spark and AWS services. Collaborate with DevOps and architects for system scalability and performance. Optimize Redshift-based data solutions for performance and reliability. Must-Have Skills & Experience: 3+ years in Data Engineering or Data Science with strong ETL and pipeline experience. Expertise in Python and SQL . Strong experience in Data Warehousing , Data Lakes , Data Modeling , and Ingestion . Working knowledge of Airflow or similar orchestration tools. Hands-on with data extraction techniques like CDC , batch-based, using Debezium, Kafka Connect, AWS DMS . Experience with AWS Services : Glue, Redshift, Lambda, EMR, Athena, MWAA, SQS, etc. Knowledge of Spark or similar distributed systems. Experience with queuing/messaging systems like SQS , Kinesis , RabbitMQ .

Experience: 5-8 Years (Lead-23 LPA), 8-10 Years (Senior Lead 35 LPA), 10+ Years (Architect- 42 LPA)- Max Location : Bangalore as 1 st preference , We can also go for Hyderabad, Chennai, Pune, Gurgaon Notice: Immediate to max 15 Days Joiner Mode of Work: Hybrid Job Description: Athena, Step Functions, Spark - Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Cloud front We are looking for an experienced AWS Data Engineer to design, build, and manage robust, scalable, and high-performance data pipelines and data platforms on AWS. The ideal candidate will have a strong foundation in ETL fundamentals, data modeling, and modern data architecture, with hands-on expertise across a broad spectrum of AWS services including Athena, Glue, Step Functions, Lambda, S3, and Lake Formation. Key Responsibilities: Design and implement scalable ETL/ELT pipelines using AWS Glue, Spark (PySpark), and Step Functions. Work with structured and semi-structured data using Athena, S3, and Lake Formation to enable efficient querying and access control. Develop and deploy serverless data processing solutions using AWS Lambda and integrate them into pipeline orchestration. Perform advanced SQL and PL/SQL development for data transformation, analysis, and performance tuning. Build data lakes and data warehouses using S3, Aurora, and Athena. Implement data governance, security, and access control strategies using AWS tools including Lake Formation, CloudFront, EBS/EFS, and IAM. Develop and maintain metadata, lineage, and data cataloging capabilities. Participate in data modeling exercises for both OLTP and OLAP environments. Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver actionable insights. Monitor, debug, and optimize data pipelines for reliability and performance. Required Skills & Experience: Strong experience with AWS data services: Glue, Athena, Step Functions, Lambda, Lake Formation, S3, EC2, Aurora, EBS/EFS, CloudFront. Proficient in PySpark, Python, SQL (basic and advanced), and PL/SQL. Solid understanding of ETL/ELT processes and data warehousing concepts. Familiarity with modern data platform fundamentals and distributed data processing. Experience in data modeling (conceptual, logical, physical) for analytical and operational use cases. Experience with orchestration and workflow management tools within AWS. Strong debugging and performance tuning skills across the data stack.

Job Title: Lead Data Engineer Job Summary The Lead Data Engineer will provide technical expertise in analysis, design, development, rollout and maintenance of data integration initiatives. This role will contribute to implementation methodologies and best practices, as well as work on project teams to analyse, design, develop and deploy business intelligence / data integration solutions to support a variety of customer needs. This position oversees a team of Data Integration Consultants at various levels, ensuring their success on projects, goals, trainings and initiatives though mentoring and coaching. Provides technical expertise in needs identification, data modelling, data movement and transformation mapping (source to target), automation and testing strategies, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective whilst leveraging best fit technologies (e.g., cloud, Hadoop, NoSQL, etc.) and approaches to address business and environmental challenges Works with stakeholders to identify and define self-service analytic solutions, dashboards, actionable enterprise business intelligence reports and business intelligence best practices. Responsible for repeatable, lean and maintainable enterprise BI design across organizations. Effectively partners with client team. Leadership not only in the conventional sense, but also within a team we expect people to be leaders. Candidate should elicit leadership qualities such as Innovation, Critical thinking, optimism/positivity, Communication, Time Management, Collaboration, Problem-solving, Acting Independently, Knowledge sharing and Approachable. Responsibilities: Design, develop, test, and deploy data integration processes (batch or real-time) using tools such as Microsoft SSIS, Azure Data Factory, Databricks, Matillion, Airflow, Sqoop, etc. Create functional & technical documentation e.g. ETL architecture documentation, unit testing plans and results, data integration specifications, data testing plans, etc. Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs. Perform data analysis to validate data models and to confirm ability to meet business needs. May serve as project or DI lead, overseeing multiple consultants from various competencies Stays current with emerging and changing technologies to best recommend and implement beneficial technologies and approaches for Data Integration Ensures proper execution/creation of methodology, training, templates, resource plans and engagement review processes Coach team members to ensure understanding on projects and tasks, providing effective feedback (critical and positive) and promoting growth opportunities when appropriate. Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels Architect, design, develop and set direction for enterprise self-service analytic solutions, business intelligence reports, visualisations and best practice standards. Toolsets include but not limited to: SQL Server Analysis and Reporting Services, Microsoft Power BI, Tableau and Qlik. Work with report team to identify, design and implement a reporting user experience that is consistent and intuitive across environments, across report methods, defines security and meets usability and scalability best practices. Required Qualifications: 10 Years industry implementation experience with data integration tools such as AWS services Redshift, Athena, Lambda, Glue, S3, ETL, etc. 5-8 years of management experience required 5-8 years consulting experience preferred Minimum of 5 years of data architecture, data modelling or similar experience Bachelor’s degree or equivalent experience, Master’s Degree Preferred Strong data warehousing, OLTP systems, data integration and SDLC Strong experience in orchestration & working experience cloud native / 3rd party ETL data load orchestration Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of on premises and cloud infrastructure architectures (e.g. Azure, AWS, GCP) Strong experience in Agile Process (Scrum cadences, Roles, deliverables) & working experience in either Azure DevOps, JIRA or Similar with Experience in CI/CD using one or more code management platforms Strong databricks experience required to create notebooks in pyspark Experience using major data modelling tools (examples: ERwin, ER/Studio, PowerDesigner, etc.) Experience with major database platforms (e.g. SQL Server, Oracle, Azure Data Lake, Hadoop, Azure Synapse/SQL Data Warehouse, Snowflake, Redshift etc.) Strong experience in orchestration & working experience in either Data Factory or HDInsight or Data Pipeline or Cloud composer or Similar Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.) Understanding of modern data warehouse capabilities and technologies such as real-time, cloud, Big Data. Understanding of on premises and cloud infrastructure architectures (e.g. Azure, AWS, GCP) Strong experience in Agile Process (Scrum cadences, Roles, deliverables) & working experience in either Azure DevOps, JIRA or Similar with Experience in CI/CD using one or more code management platforms 3-5 years’ development experience in decision support / business intelligence environments utilizing tools such as SQL Server Analysis and Reporting Services, Microsoft’s Power BI, Tableau, looker etc. Preferred Skills & Experience: Knowledge and working experience with Data Integration processes, such as Data Warehousing, EAI, etc. Experience in providing estimates for the Data Integration projects including testing, documentation, and implementation Ability to Analyse business requirements as they relate to the data movement and transformation processes, research, evaluation and recommendation of alternative solutions. Ability to provide technical direction to other team members including contractors and employees. Ability to contribute to conceptual data modelling sessions to accurately define business processes, independently of data structures and then combines the two together. Proven experience leading team members, directly or indirectly, in completing high-quality major deliverables with superior results Demonstrated ability to serve as a trusted advisor that builds influence with client management beyond simply EDM. Can create documentation and presentations such that the they “stand on their own” Can advise sales on evaluation of Data Integration efforts for new or existing client work. Can contribute to internal/external Data Integration proof of concepts. Demonstrates ability to create new and innovative solutions to problems that have previously not been encountered. Ability to work independently on projects as well as collaborate effectively across teams Must excel in a fast-paced, agile environment where critical thinking and strong problem solving skills are required for success Strong team building, interpersonal, analytical, problem identification and resolution skills Experience working with multi-level business communities Can effectively utilise SQL and/or available BI tool to validate/elaborate business rules. Demonstrates an understanding of EDM architectures and applies this knowledge in collaborating with the team to design effective solutions to business problems/issues. Effectively influences and, at times, oversees business and data analysis activities to ensure sufficient understanding and quality of data. Demonstrates a complete understanding of and utilises DSC methodology documents to efficiently complete assigned roles and associated tasks. Deals effectively with all team members and builds strong working relationships/rapport with them. Understands and leverages a multi-layer semantic model to ensure scalability, durability, and supportability of the analytic solution. Understands modern data warehouse concepts (real-time, cloud, Big Data) and how to enable such capabilities from a reporting and analytic stand-point. Demonstrated ability to serve as a trusted advisor that builds influence with client management beyond simply EDM.

Role & responsibilities Design, develop, and optimize scalable ETL pipelines using PySpark and AWS data services Work with structured and semi-structured data from various sources and formats (CSV, JSON, Parquet) Build reusable data transformations using Spark DataFrames, RDDs, and Spark SQL Implement data validation, quality checks, and ensure schema evolution across data sources Manage deployment and monitoring of Spark jobs using AWS EMR, Glue, Lambda, and CloudWatch Collaborate with product owners, architects, and data scientists to deliver robust data workflows Tune job performance, manage partitioning strategies, and reduce job latency/cost Contribute to version control, CI/CD processes, and production support Preferred candidate profile Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. 5+ years of experience in PySpark, Spark SQL, RDDs, UDFs, and Spark optimization Strong experience in building ETL workflows for large-scale data processing Solid understanding of AWS cloud ecosystem, especially S3, EMR, Glue, Lambda, Athena Proficiency in Python, SQL, and shell scripting Experience with data lakes, partitioning strategies, and file formats (e.g., Parquet, ORC) Familiarity with Git, Jenkins, and automated testing frameworks (e.g., PyTest) Experience with Redshift, Snowflake, or other DW platforms Exposure to data governance, cataloging, or DQ frameworks Terraform or infrastructure-as-code experience Understanding of Spark internals, DAGs, and caching strategies

Who we are. About Stripe. Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.. About The Team. The Reporting Platform Data Foundations group maintains and evolves the core systems that power reporting data for Stripe's users. We're responsible for Aqueduct, the data ingestion and processing platform that powers core reporting data for millions of businesses on Stripe. We integrate with the latest Data Platform tooling, such as Falcon for real-time data. Our goal is to provide a robust, scalable, and efficient data infrastructure that enables clear and timely insights for Stripe's users.. What you'll do. As a Software Engineer on the Reporting Platform Data Foundations group, you will lead efforts to improve and redesign core data ingestion and processing systems that power reporting for millions of Stripe users. You'll tackle complex challenges in data management, scalability, and system architecture.. Responsibilities. Design and implement a new backfill model for reporting data that can handle hundreds of millions of row additions and updates efficiently. Revamp the end-to-end experience for product teams adding or changing API-backed datasets, improving ergonomics and clarity. Enhance the Aqueduct Dependency Resolver system, responsible for determining what critical data to update for Stripe’s users based on events. Areas include error management, observability, and delegation of issue resolution to product teams. Lead integration with the latest Data Platform tooling, such as Falcon for real-time data, while managing deprecation of older systems. Implement and improve data warehouse management practices, ensuring data freshness and reliability. Collaborate with product teams to understand their reporting needs and data requirements. Design and implement scalable solutions for data ingestion, processing, and storage. Onboard, spin up, and mentor engineers, and set the group’s technical direction and strategy. Who you are. We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.. Minimum Requirements. 8+ years of professional experience writing high quality production level code or software programs.. Extensive experience in designing and implementing large-scale data processing systems. Strong background in distributed systems and data pipeline architectures. Proficiency in at least one modern programming language (e.g., Go, Java, Python, Scala). Experience with big data technologies (e.g., Hadoop, Flink, Spark, Kafka, Pinot, Trino, Iceberg). Solid understanding of data modeling and database systems. Excellent problem-solving skills and ability to tackle complex technical challenges. Strong communication skills and ability to work effectively with cross-functional teams. Experience mentoring other engineers and driving technical initiatives. Preferred Qualifications. Experience with real-time data processing and streaming systems. Knowledge of data warehouse technologies and best practices. Experience in migrating legacy systems to modern architectures. Contributions to open-source projects or technical communities. In-office expectations. Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.. Pay and benefits. Stripe does not yet include pay ranges in job postings in every country. Stripe strongly values pay transparency and is working toward pay transparency globally.. Show more Show less

3-4 years hands-on experience on AWS services, ideally SaaS in the cloud Experience developing solutions with code/scripting language must have Python experience (e.g, python, Node.js) Experience in creating and configuring AWS resources like API Gateway, CloudWatch, Cloud-Formation, EC2, Lambda, Amazon Connect, SNS, Athena, Glue, VPC etc.Sourcing & Screening US profiles Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad ,Remote

Work closely with the Product Owners and stake holders to design the Technical Architecture for data platform to meet the requirements of the proposed solution. Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines Play an active role in leading team meetings and workshops with clients. Choose and use the right analytical libraries, programming languages, and frameworks for each task. Help the Data Engineering team produce high-quality code that allows us to put solutions into production Create and own the technical product backlogs for products, help the team to close the backlogs in right time. Refactor code into reusable libraries, APIs, and tools. Help us to shape the next generation of our products. What Were Looking For Total experience in data management area for 10 + years experience in the implementation of modern data ecosystems in AWS/Cloud platforms. Strong experience with AWS ETL/File Movement tools (GLUE, Athena, Lambda, Kinesis and other AWS integration stack) Strong experience with Agile Development, SQL Strong experience with Two or Three AWS database technologies (Redshift, Aurora, RDS,S3 & other AWS Data Service ) covering security, policies, access management Strong programming Experience with Python and Spark Strong learning curve for new technologies Experience with Apache Airflow & other automation stack. Excellent with Data Modeling. Excellent oral and written communication skills. A high level of intellectual curiosity, external perspective, and innovation interest Strong analytical, problem solving and investigative skills Experience in applying quality and compliance requirements.

At Alcon, we aspire to lead the world in innovating life-changing vision products because when people see brilliantly, they live brilliantly. As a global leader in eye care, we believe in innovating especially through cutting edge technology. We are on a journey to offer the widest array of eye care and eye health offerings with products that can treat the entire eye at each stage of life. Our Digital Health team is harnessing technology to build a leading portfolio of digital health solutions that will transform the eye care experience for medical professionals to patients and enable improved patient outcomes from a predictive health care delivery platform harnessing ML and analytics to innovative medical device software. As Principal Data Analyst Digital Health, you will be responsible for collecting, analyzing and interpreting large data sets to identify trends and insights that inform business decisions. You will collaborate with cross-functional teams to develop and implement data-driven solutions that improve business outcomes. We are a fast-growing team, which will give you the opportunity to shape our ways of working and culture - think start-up, but inside a global leader in eye care. We are looking for someone who is a strategic thinker and problem solver. Key Responsibilities Partner with business stakeholders to develop KPI dashboards & reports that drive data-informed decision-making. Collaborate with the data product team to define requirements for data products and analytics use cases. Collaborate with the data engineering team to develop robust data pipelines and products while maintaining regulatory and compliance standards. Work alongside data scientists to support the development of AI/ML models. Build and maintain databases and data systems to enhance data accuracy, completeness, and usability for analytics. Identify opportunities to streamline data collection, processing, and analysis, implementing best practices to enhance efficiency. Foster a culture of creativity, collaboration, speed, innovation, and engineering excellence. Coach and mentor junior data analysts. Key Requirements/Qualifications Minimum Qualifications Bachelor's degree in statistics, business analytics, data science, or a related technical discipline. Strong communication and collaboration skills to deliver business solutions Approaches challenges with a positive and can-do attitude. Willing to challenge the status quo, demonstrating ability to understand when and how to take appropriate risks to drive performance. Thrives in dynamic, cross-functional team environments. Possesses a team-first mindset, valuing diverse perspectives and contributing to a collaborative work culture. Strong analytical and problem-solving skills, with attention to detail and accuracy. Proficient in SQL, altrex, DBeaver, Athena, Quantum metric 3+ years building cloud analytics solutions on AWS or Azure. 5+ years of hands-on experience in dashboard/BI and data visualization tools (eg. Tableau, React, Quicksight, Power BI) 7+ years of hands-on experience in data preparation and analysis of large-scale datasets. Preferred Qualifications Experience in healthcare and related data analytics use cases Experience in building and launching data analytics and reporting products. Location India

Join us as a Data Engineer II in Bengaluru! Build scalable data pipelines using Python, SQL, AWS, Airflow, and Kafka. Drive real-time & batch data systems across analytics, ML, and product teams. A hybrid work option is available. Required Candidate profile 3+ yrs in data engineering with strong Python, SQL, AWS, Airflow, Spark, Kafka, Debezium, Redshift, ETL & CDC experience. Must know data lakes, warehousing, and orchestration tools.

Join us as an AWS/PySpark Engineer at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences As a part of team of developers, you will deliver technology stack, using strong analytical and problem solving skills to understand the business requirements and deliver quality solutions, To be successful as an AWS/PySpark Engineer you should have experience with: AWS, Glue, Athena, Airflow, ETL, Hadoop PySpark SQL, Unix Scheduling, Data Pipelines, Debugging Skills Some Other Highly Valued Skills May Include Abinitio, Unix You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills, This role is based out of Chennai, Purpose of the role To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure, Accountabilities Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data, Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures, Development of processing and analysis algorithms fit for the intended data complexity and volumes, Collaboration with data scientist to build and deploy machine learning models, Analyst Expectations To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement, Requires in-depth technical knowledge and experience in their assigned area of expertise Thorough understanding of the underlying principles and concepts within the area of expertise They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources, If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard The four LEAD behaviours are: L Listen and be authentic, E Energise and inspire, A Align across the enterprise, D Develop others, OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate, Will have an impact on the work of related teams within the area, Partner with other functions and business areas, Takes responsibility for end results of a teams operational processing and activities, Escalate breaches of policies / procedure appropriately, Take responsibility for embedding new policies/ procedures adopted due to risk mitigation, Advise and influence decision making within own area of expertise, Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct, Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function, Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function, Make evaluative judgements based on the analysis of factual information, paying attention to detail, Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents, Guide and persuade team members and communicate complex / sensitive information, Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation, All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship our moral compass, helping us do what we believe is right They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge and Drive the operating manual for how we behave,

Those aren't words that are usually associated with a job But working at Bristol Myers Squibb is anything but usual Here, uniquely interesting work happens every day, in every department From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams Take your career farther than you thought possible, Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives Read more careers bms,/working-with-us , Position Summary The GPS Data & Analytics Software Engineer role is accountable for developing data solutions and operations support of the Enterprise data lake The role will be accountable for developing the pipelines for the data enablement projects, production/application support and enhancements, and support data operations activities Additional responsibilities include data analysis, data operations process and tools, data cataloguing, and developing data SME skills in Global Product Development and Supply Data and Analytics Enablement organization, Key Responsibilities The Data Engineer will be responsible for designing, building, and maintaining the data products, evolution of the data products, and utilize the most suitable data architecture required for our organization's data needs to support GPS Responsible for delivering high quality, data products and analytic ready data solutions Develop and maintain data models to support our reporting and analysis needs, Develop ad-hoc analytic solutions from solution design to testing, deployment, and full lifecycle management, Optimize data storage and retrieval to ensure efficient performance and scalability Collaborate with data architects, data analysts and data scientists to understand their data needs and ensure that the data infrastructure supports their requirements Ensure data quality and integrity through data validation and testing Implement and maintain security protocols to protect sensitive data Stay up-to-date with emerging trends and technologies in data engineering and analytics Participate in the analysis, design, build, manage, and operate lifecycle of the enterprise data lake and analytics focused digital capabilities Develop cloud-based (AWS) data pipelines to facilitate data processing and analysis Build e-2-e data ETL pipelines from data integration -> data processing -> data integration -> visualization Proficient Python/nodeDot js along with UI technologies like ReactsDot js, Spark, SQL, AWS Redshift, AWS S3, Glue/Glue Studio, Athena, IAM, other Native AWS Service familiarity with Domino/data lake principles, Good to have any Knowledge on Neo4J, IAM, CFT & other Native AWS Service familiarity with data lake principles, Familiarity and experience with Cloud infrastructure management and work closely with the Cloud engineering team Participate in effort and cost estimations when required Partner with other data, platform, and cloud teams to identify opportunities for continuous improvements Architect and develop data solutions according to legal and company guidelines Assess system performance and recommend improvements Responsible for maintaining of data acquisition/operational focused capabilities including Data Catalog; User Access Request/Tracking; Data Use Request If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway You could be one step away from work that will transform your life and career, Uniquely Interesting Work, Life-changing Careers With a single vision as inspiring as Transforming patients' lives through science, every BMS employee plays an integral role in work that goes far beyond ordinary Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues, On-site Protocol BMS has an occupancy structure that determines where an employee is required to conduct their work This structure includes site-essential, site-by-design, field-based and remote-by-design jobs The occupancy type that you are assigned is determined by the nature and responsibilities of your role Site-essential roles require 100% of shifts onsite at your assigned facility Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function, BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer

7+ years in software engineering, with 4+ years using AWS. Programming languages: C# and Python, along with SQL and Spark. The engineering position requires a minimum three-hour overlap with team members in the US-Pacific time zone. Strong experience with some (or all) of the following: Lambda and Step functions, API Gateway, Fargate, ECS, S3, SQS, Kinesis, Firehose, DynamoDB, RDS, Athena, and Glue. Solid foundation in data structures and algorithms and in-depth knowledge and passion for coding standards and following proven design patterns. RESTful and GraphQL APIs are examples. You might also have... DevOps experience is a plus, GitHub, GitHub Actions, Docker. Experience building CI/CD and server/deployment automation solutions, and container orchestration technologies.

Job description: Seeking a skilled & proactive Data Engineer with 24 years of experience to support our enterprise data warehousing and analytics initiatives. The Candidate will be responsible for building scalable data pipelines, transforming data for analytics, and enabling data integration across cloud and On-premise systems. Key Responsibilities: Build and manage data lakes and data warehouses using services like Amazon S3, Redshift, and Athena Design and build secure, scalable, and efficient ETL/ELT pipelines on AWS using services like Glue, Lambda, Step Functions Work on SAP Datasphere to build and maintain Spaces, Data Builders, Views, and Consumption Layers Support data integration between AWS, Datasphere, and various source systems(SAP S4HANA, Non-SAP apps, Flat-files etc) Develop and maintain scalable data models and optimize queries for performance Monitor and optimize data workflows to ensure reliability, performance, and cost-efficiency Collaborate with Data Analysts and BI teams to provide clean, validated, and well-documented datasets Monitor, troubleshoot, and enhance data workflows and pipelines Ensure data quality, integrity, and governance policies are met Required Skills Strong SQL skills and experience with relational databases like MySQL, or SQL Server Proficient in Python or Scala for data transformation and scripting Familiarity with cloud platforms like AWS (S3, Redshift, Glue), Datasphere, Azure Good-to-Have Skills AWS Certification – AWS Certified Data Analytics Exposure to modern data stack tools like Snowflake Experience in cloud-based projects and working in an Agile environment Understanding of data governance, security best practices, and compliance standards

Job Duties and Responsibilities: We are looking for a self-starter to join our Data Engineering team. You will work in a fast-paced environment where you will get an opportunity to build and contribute to the full lifecycle development and maintenance of the data engineering platform. With the Data Engineering team you will get an opportunity to - Design and implement data engineering solutions that is scalable, reliable and secure on the Cloud environment Understand and translate business needs into data engineering solutions Build large scale data pipelines that can handle big data sets using distributed data processing techniques that supports the efforts of the data science and data application teams Partner with cross-functional stakeholder including Product managers, Architects, Data Quality engineers, Application and Quantitative Science end users to deliver engineering solutions Contribute to defining data governance across the data platform Basic Requirements: A minimum of a BS degree in computer science, software engineering, or related scientific discipline is desired 3+ years of work experience in building scalable and robust data engineering solutions Strong understanding of Object Oriented programming and proficiency with programming in Python (TDD) and Pyspark to build scalable algorithms 3+ years of experience in distributed computing and big data processing using the Apache Spark framework including Spark optimization techniques 2+ years of experience with Databricks, Delta tables, unity catalog, Delta Sharing, Delta live tables(DLT) and incremental data processing Experience with Delta lake, Unity Catalog Advanced SQL coding and query optimization experience including the ability to write analytical and nested queries 3+ years of experience in building scalable ETL/ ELT Data Pipelines on Databricks and AWS (EMR) 2+ Experience of orchestrating data pipelines using Apache Airflow/ MWAA Understanding and experience of AWS Services that include ADX, EC2, S3 3+ years of experience with data modeling techniques for structured/ unstructured datasets Experience with relational/columnar databases - Redshift, RDS and interactive querying services - Athena/ Redshift Spectrum Passion towards healthcare and improving patient outcomes Demonstrate analytical thinking with strong problem solving skills Stay on top of emerging technologies and posses willingness to learn. Bonus Experience (optional) Experience with Agile environment Experience operating in a CI/CD environment Experience building HTTP/REST APIs using popular frameworks Healthcare experience

Roles & Responsibilities : • We are looking for a strong Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines . • Integration of data from multiple sources or vendors to provide the holistic insights from data. • You are expected to build and manage Data Lake and Data warehouse solutions, design data models, create ETL processes, implementing data quality mechanisms etc. • Perform EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues. • Should have experience in client interaction oral and written. • Experience in mentoring juniors and providing required guidance to the team. Required Technical Skills • Extensive experience in languages such as Python, Pyspark, SQL (basics and advanced). • Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Data Architecture . • Must be proficient in Redshift, Azure Data Factory, Snowflake etc. • Hands-on experience in cloud services like AWS S3, Glue, Lambda, CloudWatch, Athena etc. • Good to have knowledge in Dataiku, Big Data Technologies and basic knowledge of BI tools like Power BI, Tableau etc will be plus. • Sound knowledge in Data management, data operations, data quality and data governance. • Knowledge of SFDC, Waterfall/ Agile methodology. • Strong knowledge of Pharma domain / life sciences commercial data operations. Qualifications • Bachelors or masters Engineering/ MCA or equivalent degree. • 4-6 years of relevant industry experience as Data Engineer . • Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales, Open Data etc. • High motivation, good work ethic, maturity, self-organized and personal initiative. • Ability to work collaboratively and providing the support to the team. • Excellent written and verbal communication skills. • Strong analytical and problem-solving skills. Location • Preferably Hyderabad/ Chennai, India

About the Role: We are looking for a hands-on AWS Data Architect OR Lead Engineer to design and implement scalable, secure, and high-performing data solutions. This is an individual contributor role where you will work closely with data engineers, analysts, and stakeholders to build modern, cloud-native data architectures across real-time and batch pipelines. Experience: 715 Years Location: Fully Remote Company: Armakuni India Key Responsibilities: Data Architecture Design: Develop and maintain a comprehensive data architecture strategy that aligns with the business objectives and technology landscape. Data Modeling: Create and manage logical, physical, and conceptual data models to support various business applications and analytics. Database Design: Design and implement database solutions, including data warehouses, data lakes, and operational databases. Data Integration: Oversee the integration of data from disparate sources into unified, accessible systems using ETL/ELT processes. Data Governance: Implemented enforce data governance policies and procedures to ensure data quality, consistency, and security. Technology Evaluation: Evaluate and recommend data management tools, technologies, and best practices to improve data infrastructure and processes. Collaboration: Work closely with data engineers, data scientists, business analysts, and other stakeholders to understand data requirements and deliver effective solutions. Trusted by the worlds leading brands Documentation: Create and maintain documentation related to data architecture, data flows, data dictionaries, and system interfaces. Performance Tuning: Optimize database performance through tuning, indexing, and query optimization. Security: Ensure data security and privacy by implementing best practices for data encryption, access controls, and compliance with relevant regulations (e.g., GDPR, CCPA) Required Skills: Helping project teams with solutions architecture, troubleshooting, and technical implementation assistance. Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, Oracle, SQL Server). Minimum7to15 years of experience in data architecture or related roles. Experience with big data technologies (e.g., Hadoop, Spark, Kafka, Airflow). Expertise with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services. Knowledge of data integration tools (e.g., Informatica, Talend, FiveTran, Meltano). Understanding of data warehousing concepts and tools (e.g., Snowflake, Redshift, Synapse, BigQuery). Experience with data governance frameworks and tools.

As Lead Data Engineer , you'll design and manage scalable ETL pipelines and clean, structured data flows for real-time retail analytics. You'll work closely with ML engineers and business teams to deliver high-quality, ML-ready datasets. Responsibilities: Develop and optimize large-scale ETL pipelines Design schema-aware data flows and dashboard-ready datasets Manage data pipelines on AWS (S3, Glue, Redshift) Work with transactional and retail data for real-time insights

We are seeking an experienced and analytical Senior Data Analyst to join our Data & Analytics team. The ideal candidate will have a strong background in data analysis, visualization, and stakeholder communication. You will be responsible for turning data into actionable insights that help shape strategic and operational decisions across the organization. Job Description / Duties & Responsibilities Collaborate with business stakeholders to understand data needs and translate them into analytical requirements. Analyze large datasets to uncover trends, patterns, and actionable insights. Design and build dashboards and reports using Power BI. Perform ad-hoc analysis and develop data-driven narratives to support decision-making. Ensure data accuracy, consistency, and integrity through data validation and quality checks. Build and maintain SQL queries, views, and data models for reporting purposes. Communicate findings clearly through presentations, visualizations, and written summaries. Partner with data engineers and architects to improve data pipelines and architecture. Contribute to the definition of KPIs, metrics, and data governance standards. Job Specification / Skills and Competencies Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related field. 5+ years of experience in a data analyst or business intelligence role. Advanced proficiency in SQL and experience working with relational databases (e.g., SQL Server, Redshift, Snowflake). Hands-on experience in Power BI. Proficiency in Python, Excel and data storytelling. Understanding of data modelling, ETL concepts, and basic data architecture. Strong analytical thinking and problem-solving skills. Excellent communication and stakeholder management skills To adhere to the Information Security Management policies and procedures. Soft Skills Required ? Must be a good team player with good communication skills ? Must have good presentation skills ? Must be a pro-active problem solver and a leader by self ? Manage & nurture a team of data engineers

Job Title: Senior Data Analyst (SQL + Power BI + Python) Experience:5+ years Work Location:Trivandrum/Kochi Notice Period:Immediate Joiners Only Budget:Up to19 LPA Mandatory Skillset: ?Advanced SQL(Complex Queries, Optimization, Amazon Athena) ?Power BI(DAX, Data Modeling, Dashboard Development) ?Python(Pandas, NumPy for Data Analysis) ?Data Visualization & Storytelling ?ETL Concepts & Data Warehousing (Experience with cloud data platforms like Redshift/Snowflake is a plus) Job Purpose: As aSenior Data Analyst, you will transform raw data intoactionable business insights, design interactive dashboards, and collaborate with cross-functional teams to drive data-led decision-making across the organization. Key Responsibilities: 1. Data Analysis & Insights Analyze large datasets usingSQL (Amazon Athena), Python, and Excelto uncover trends. Developdata-driven narrativesfor strategic decision-making. 2. Visualization & Reporting Design and maintaininteractive Power BI dashboardswith DAX measures. Automate reports and implementself-service analyticsfor stakeholders. 3. Data Pipeline Collaboration Partner withdata engineersto optimize SQL queries, views, and ETL pipelines. Ensuredata quality and governancethrough validation checks. 4. Stakeholder Management Translate business requirements intoanalytical frameworks/KPIs. Present findings to leadership throughclear visualizations and presentations. 5. Leadership & Mentorship Guide junior analysts and fosterbest practices in data analysis. Contribute todata strategy and governance standards. Required Skills: ?Technical Expertise: 5+ years inSQL, Power BI, and Python (Pandas/NumPy). Experience withcloud databases(Athena, Redshift, Snowflake). ?Analytical Mindset: Strongproblem-solvingandstatistical analysisskills. Knowledge ofdata modeling and ETL processes. ?Soft Skills: Excellentcommunication and presentation skills. Ability tolead projects and mentor teams. Preferred Qualifications: Degree inStatistics, Computer Science, Economics, or related fields. Experience withadvanced analytics (predictive modeling, ML basics). Knowledge ofGit/Azure DevOpsfor version control.

Data Analysis: Conduct in-depth analysis of data to identify trends, anomalies, and opportunities, utilizing SQL, AWS, and Python to extract and manipulate data. Business Transformation: Translate existing SQL queries into business transformation logics, enabling the conversion of raw data into actionable insights to drive strategic decision-making. Requirements Gathering: Collaborate with business stakeholders to gather and document. clear and concise business requirements, ensuring a thorough understanding of data needs. Documentation: Develop and maintain documentation related to data analysis, transformation, and reporting processes, ensuring knowledge transfer and continuity. AWS Integration: Leverage AWS services to facilitate data extraction, storage, and analysis, making data readily available for the business. Quality Assurance: Implement data quality checks and validation processes to ensure the accuracy and integrity of data used in analyses. Qualifications: Bachelors degree in business, Computer Science, or a related field. Proven experience as a Business Analyst with a strong focus on data analysis and transformation. Proficiency in SQL for querying and manipulating relational databases. Awareness of AWS services such as Redshift, S3, Athena, Lambda, Step Functions, AWS Batch Proficiency in Python for data analysis and scripting. Experience in converting SQL queries into actionable business transformation logics. Strong problem-solving and critical-thinking skills. Excellent communication and interpersonal skills to work effectively with cross-functional. teams and stakeholders. Attention to detail and a commitment to data accuracy and quality.

The resource should have a strong background in working with cloud platforms, APIs, and data processing. Experience with tools like AWS Glue, Athena, and Databricks will be highly beneficial. AWS Glue Jobs: The QE should have familiarity with AWS Glue jobs for ETL processes. We expect them to validate the successful execution of around Glue jobs, ensuring that transformations and data ingestion tasks are working smoothly without errors. Athena Querying: Experience with querying data using AWS Athena is a must, as the QE will be required to validate queries across multiple datasets. We expect the resource to run and validate Athena queries for data accuracy and integrity. Databricks Testing: The candidate should also have experience with Databricks, particularly in validating data pipelines and transformations within the Databricks environment. The QE will need to test Databricks notebooks or jobs, ensuring data accuracy in the Bronze, Silver, and Gold layers. Boomi integrations