19 Sparksql Jobs

Design, develop, and maintain Power BI dashboards and interactive reports for cross-functional departments (e.g., Sales, Operations, HR, Finance). Connect, transform, and model data from both online sources (APIs, cloud platforms, Databricks, databases) and offline sources (Excel, CSV, etc.). Integrate data from Databricks , MySQL , and SparkSQL for comprehensive analytics and visual storytelling. Handle large-scale structured and unstructured data with high performance and efficiency. Automate recurring reporting processes using Power BI Service, Dataflows, and scheduled refreshes. Develop reusable and scalable data models , datasets , and report templates . Write efficient DAX and Power Query (M) expressions to support complex business logic. Ensure dashboards meet user needs and are optimized for performance and usability. Collaborate with business users and technical teams to gather requirements and deliver insights. Maintain organization data governance, security, and compliance standards across all BI solutions. Role & responsibilities Preferred candidate profile Experience with Azure Data Factory , Azure Synapse , or similar data orchestration tools. Knowledge of Git-based version control and CI/CD pipelines for BI deployments. Microsoft certifications (e.g., DA-100 / PL-300 / Azure Data Engineer). 35 years of hands-on experience developing dashboards using Power BI . Strong practical knowledge of Databricks , MySQL , and SparkSQL . Proven experience working with large datasets , including structured (relational DBs) and unstructured (logs, JSON, files). Expertise in connecting to both online (cloud/real-time) and offline (local/file-based) data sources. Proficiency in DAX , Power Query (M) , and advanced data modeling. Strong understanding of data architecture , ETL workflows , and BI best practices . Excellent communication skills to interact with stakeholders across departments. Ability to work independently and manage multiple dashboard/reporting projects simultaneously.

Role Technology Lead No of years experience 5+ Detailed job description - Skill Set: Role Summary: As part of the offshore development team, the AWS Developers will be responsible for implementing ingestion and transformation pipelines using PySpark, orchestrating jobs via MWAA, and converting legacy Cloudera jobs to AWS-native services. Key Responsibilities: Write ingestion scripts (batch & stream) to migrate data from on-prem to S3. Translate existing HiveQL into SparkSQL/PySpark jobs. Configure MWAA DAGs to orchestrate job dependencies. Build Iceberg tables with appropriate partitioning and metadata handling. Validate job outputs and write unit tests. Required Skills: 35 years in data engineering, with strong exposure to AWS. Experience in EMR (Spark), S3, PySpark, SQL. Working knowledge of Cloudera/HDFS and legacy Hadoop pipelines. Prior experience with data lake/lakehouse implementations is a plus Mandatory Skills AWS Developer

What you will do About the role You will play a key role as part of Operations Generative AI (GenAI) Product team to deliver cutting edge innovative GEN AI solutions across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations functions. Role Description: The Sr Data Engineer for GEN AI solutions across various Process Development functions(Drug Substance, Drug Product, Attribute Sciences & Combination Products) in Operations functions is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions, working with large datasets, developing reports, supporting and implementing data governance initiatives and visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes. Roles & Responsibilities: Design, develop, and maintain data solutions for data generation, collection, and processing. Be a key team member that assists in design and development of the data pipeline. Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems. Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions. Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks. Collaborate with multi-functional teams to understand data requirements and design solutions that meet business needs. Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency. Implement data security and privacy measures to protect sensitive data. Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions. Develop solutions for handling unstructured data in AI pipelines. Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions. Identify and resolve complex data-related challenges. Adhere to standard processes for coding, testing, and designing reusable code/component. Explore new tools and technologies that will help to improve ETL platform performance. Participate in sprint planning meetings and provide estimations on technical implementation. Collaborate and communicate effectively with product teams. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Masters degree with 4 - 6 years of experience in Computer Science, IT or related field OR Bachelors degree with 6 - 8 years of experience in Computer Science, IT or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT or related field. Must-Have Skills: Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing. Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools. Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and DevOps Excellent problem-solving skills and the ability to work with large, complex datasets. Strong understanding of data governance frameworks, tools, and standard methodologies. Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models. Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow. Experience in processing and leveraging unstructured data for GenAI applications Preferred Qualifications: Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development. Strong understanding of data modeling, data warehousing, and data integration concepts. Knowledge of Python/R, Databricks. Knowledge of vector databases, including implementation and optimization. Professional Certifications: Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments). Machine Learning Certification (preferred on Databricks or Cloud environments). SAFe for Teams certification (preferred). Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals

What you will do In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and performing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes. Roles & Responsibilities: Design, develop, and maintain data solutions for data generation, collection, and processing Be a crucial team member that assists in design and development of the data pipeline Build data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency Implement data security and privacy measures to protect sensitive data Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions Collaborate and communicate effectively with product teams Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions Identify and resolve complex data-related challenges Adhere to best practices for coding, testing, and designing reusable code/component Explore new tools and technologies that will help to improve ETL platform performance Participate in sprint planning meetings and provide estimations on technical implementation Basic Qualifications: Masters degree and 1 to 3 years of Computer Science, IT or related field experience OR Bachelors degree and 3 to 5 years of Computer Science, IT or related field experience OR Diploma and 7 to 9 years of Computer Science, IT or related field experience Preferred Qualifications: Must-Have Skills: Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools Excellent problem-solving skills and the ability to work with large, complex datasets Solid understanding of data governance frameworks, tools, and best practices. Knowledge of data protection regulations and compliance requirements Good-to-Have Skills: Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development Good understanding of data modeling, data warehousing, and data integration concepts Knowledge of Python/R, Databricks, SageMaker, cloud data platforms Professional Certifications Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments) Soft Skills: Excellent critical-thinking and problem-solving skills Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills

Key Skills: SCALA, AWS, AWS Cloud, Apache Spark, Architect, SparkSQL, Spark, Spring Boot, Java Roles and Responsibilities: Technical lead the team and project to meet deadlines. Lead efforts with team members to come up with software solutions. Optimize and maintain existing software. Recommend tech upgrades to company leaders. Build scalable, efficient, and high-performance pipelines and workflows that are capable of processing large amounts of batch and real-time data. Multidisciplinary work supporting real-time streams, ETL pipelines, data warehouses, and reporting services. Design and develop microservices and data applications that interact with other microservices. Use Big Data technologies such as Kafka, Data Lake on AWS S3, EMR, Spark, and related technologies to ingest, store, aggregate, transform, move, and query data. Follow coding best practices - Unit testing, design/code reviews, code coverage, documentation, etc. Performance analysis and capacity planning for every release. Work effectively as part of an Agile team. Bring new and innovative solutions to resolve challenging software issues as they may develop throughout the product lifecycle. Skills Required: Excellence in software design skills. Strong knowledge of design patterns, including performance optimization considerations. Proficient in writing high-quality, well-structured code in Java and Scala. Excellence in test-driven development approach and debugging software. Proficient in writing clear, concise, and organized documentation. Knowledge of Amazon cloud computing infrastructure (Aurora MySQL, DynamoDB, EMR, Lambda, Step Functions, and S3). Ability to excel in a team environment. Strong communication skills and the ability to discuss a solution with team members of varying technical sophistication. Ability to perform thoughtful and detailed code reviews, both for peers and Junior Developers. Familiarity with software engineering and project management tools. Following security protocols and best data governance practices. Able to construct KPIs and using metrics for process improvements. Minimum qualifications: 12+ years' experience in designing and developing enterprise-level software solutions. 5 years' experience developing Scala/Java applications and microservices using Spring Boot. 10 years' experience with large volume data processing and big data tools such as Apache Spark, Scala, and Hadoop technologies. 5 years' experience with SQL and Relational databases. 2 years' experience working with Agile/Scrum methodology. Education: Bachelor's Degree in related field

Pyspark SparkSQL SQL and Glue AWS cloud experience Good understanding of dimensional modelling Good understanding DevOps CloudOps DataOps CI/CD & with a SRE mindset Understanding of Lakehouse and DW architecture strong analysis and analytical skills understanding of version control systems specifically Git strong in software engineering APIs Microservices etc Soft skills written and oral communication skills ability to translate business needs to system

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Design, Architect, and Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Build and optimize ETL workflows using Azure Databricks and PySpark. This includes developing efficient data processing pipelines, data validation, error handling, and performance tuning. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Articulates business requirements in a technical solution that can be designed and engineered. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 4 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them No Sql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams. What we can do for you: Youll join an entrepreneurial, inclusive culture. One where we succeed together across the desk and around the globe. Where like-minded people work naturally together to achieve great things. Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay. Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you. Scheduled Weekly Hours: 40

5+ years with Python, PySpark, SQL and SparkSQL

What you need BS in an Engineering or Science discipline, or equivalent experience 5+ years of software/data engineering experience using Java, Scala, and/or Python, with at least 3 years experience in a data and BI focused role Experience in data integration (ETL/ELT) development using multiple languages (e.g., Python, PySpark, SparkSQL) and data transformation (e.g., dbt) Experience building data pipelines supporting a variety of integration and information delivery methods as well as data modelling techniques and analytics Knowledge and experience with various relational databases and demonstrable proficiency in SQL and data analysis requiring complex queries, and optimization Experience with AWS-based data services technologies (e.g., Glue, RDS, Athena, etc.) and Snowflake CDW, as well as BI tools (e.g., PowerBI) Willingness to experiment and learn new approaches and technology applications Knowledge of software engineering and agile development best practices Excellent written and verbal communication skills

Key Skills: SCALA, Apache Spark, SQL, SparkSQL, Spark, Core Java, Java Roles and Responsibilities: Lead technical initiatives and contribute as a senior team member to achieve project goals and deadlines. Collaborate with team members to design, implement, and optimize software solutions aligned with organizational objectives. Build scalable, efficient, and high-performance pipelines and workflows for processing large amounts of batch and real-time data. Perform multidisciplinary work, supporting real-time streams, ETL pipelines, data warehouses, and reporting services. Recommend and advocate for technology upgrades to company leaders to ensure infrastructure remains robust and competitive. Design and develop microservices and data applications while ensuring seamless integration with other systems. Leverage Big Data technologies like Kafka, AWS S3, EMR, and Spark to handle data ingestion, transformation, and querying. Follow coding best practices, including unit testing, code reviews, code coverage, and maintaining comprehensive documentation. Conduct thorough code reviews to maintain quality, mentor junior team members, and promote continuous learning within the team. Enhance system performance through analysis and capacity planning, ensuring efficient and reliable software releases. Actively bring new and innovative solutions to address challenging software issues that arise throughout the product lifecycle. Implement and promote security protocols and data governance standards across development projects. Actively engage in Agile processes to foster collaboration and innovation within the team. Required job skills: Strong software design capabilities with a deep understanding of design patterns and performance optimizations. Proficiency in writing high-quality, well-structured code in Java and Scala. Expertise in SQL and relational databases, with advanced skills in writing efficient, complex queries and optimizing database performance. Expertise in cloud computing infrastructure, particularly AWS (Aurora MySQL, DynamoDB, EMR, Lambda, etc.). Solid experience with Big Data tools such as Apache Spark and Kafka. Ability to clearly document and communicate technical solutions to diverse audiences. Experience mentoring and conducting constructive code reviews to support team development. Familiarity with Agile methodologies and modern development tools. Skills Required: 10+ years experience in designing and developing enterprise level software solutions 3 years experience developing Scala / Java applications and microservices using Spring Boot 7 years experience with large volume data processing and big data tools such as Apache Spark, SQL, Scala, and Hadoop technologies 5 years experience with SQL and Relational databases 2 year Experience working with the Agile/Scrum methodology Education: Bachelors Degree in related field

We are seeking a Software Engineer with 4-7 year of experience to join our ETL Development team. This role will report to the Manager of data engineering and be involved in the planning, design, and implementation of our centralized data warehouse solution for ETL, reporting and analytics across all applications within the company. Qualifications: Deep knowledge and experience working with SSIS, T-SQL, Azure Databricks, Azure Data Lake, Azure Data Factory,. Experienced in writing SQL objects SP, UDF, Views Experienced in data modeling. Experience working with MS-SQL and NoSQL database systems such as Apache Parquet. Experience in Scala, SparkSQL, Airflow is preferred. Experience with acquiring and preparing data from primary and secondary disparate data sources Experience working on large scale data product implementation. Experience working with agile methodology preferred. Healthcare industry experience preferred. Responsibilities: Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions Work with other team with deep experience in ETL process and data science domains to understand how to centralize their data Share your passion for staying experimenting with and learning new technologies. Perform thorough data analysis, uncover opportunities, and address business problems. Working in an evolving healthcare setting, we use our shared expertise to deliver innovative solutions. Our fast-growing team has opportunities to learn and grow through rewarding interactions, collaboration and the freedom to explore professional interests.

What you will do Lets do this. Lets change the world. In this vital role you will create and develop data lake solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance data engineering solutions for large scientific datasets and collaborate with Research collaborators. You will also provide technical leadership to junior team members. The ideal candidate possesses experience in the pharmaceutical or biotech industry, demonstrates deep technical skills, is proficient with big data technologies, and has a deep understanding of data architecture and ETL processes. Roles & Responsibilities: Lead, manage, and mentor a high-performing team of data engineers Design, develop, and implement data pipelines, ETL processes, and data integration solutions Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks Develop and maintain data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency Optimize large datasets for query performance Collaborate with global multi-functional teams including research scientists to understand data requirements and design solutions that meet business needs Implement data security and privacy measures to protect sensitive data Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions Identify and resolve data-related challenges Adhere to best practices for coding, testing, and designing reusable code/component Explore new tools and technologies that will help to improve ETL platform performance Participate in sprint planning meetings and provide estimations on technical implementation What we expect of you We are all different, yet we all use our unique contributions to serve patients. The [vital attribute] professional we seek is a [type of person] with these qualifications. Basic Qualifications: Doctorate Degree OR Masters degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Bachelors degree with 6 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field Preferred Qualifications: 3+ years of experience in implementing and supporting biopharma scientific research data analytics (software platforms) Functional Skills: Must-Have Skills: Proficiency in SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing Excellent problem-solving skills and the ability to work with large, complex datasets Able to engage with business collaborators and mentor team to develop data pipelines and data models Good-to-Have Skills: A passion for tackling complex challenges in drug discovery with technology and data Good understanding of data modeling, data warehousing, and data integration concepts Good experience using RDBMS (e.g. Oracle, MySQL, SQL server, PostgreSQL) Knowledge of cloud data platforms (AWS preferred) Experience with data visualization tools (e.g. Dash, Plotly, Spotfire) Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming Experience writing and maintaining technical documentation in Confluence Understanding of data governance frameworks, tools, and best practices Professional Certifications: Databricks Certified Data Engineer Professional preferred Soft Skills: Excellent critical-thinking and problem-solving skills Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills

We are seeking a Software Engineer with 4-7 year of experience to join our ETL Development team. This role will report to the Manager of data engineering and be involved in the planning, design, and implementation of our centralized data warehouse solution for ETL, reporting and analytics across all applications within the company. Qualifications: Deep knowledge and experience working with SSIS, T-SQL, Azure Databricks, Azure Data Lake, Azure Data Factory,. Experienced in writing SQL objects SP, UDF, Views Experienced in data modeling. Experience working with MS-SQL and NoSQL database systems such as Apache Parquet. Experience in Scala, SparkSQL, Airflow is preferred. Experience with acquiring and preparing data from primary and secondary disparate data sources Experience working on large scale data product implementation. Experience working with agile methodology preferred. Healthcare industry experience preferred. Responsibilities: Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions Work with other team with deep experience in ETL process and data science domains to understand how to centralize their data Share your passion for staying experimenting with and learning new technologies. Perform thorough data analysis, uncover opportunities, and address business problems. Working in an evolving healthcare setting, we use our shared expertise to deliver innovative solutions. Our fast-growing team has opportunities to learn and grow through rewarding interactions, collaboration and the freedom to explore professional interests.

What you need BS in an Engineering or Science discipline, or equivalent experience 5+ years of software/data engineering experience using Java, Scala, and/or Python, with at least 3 years experience in a data and BI focused role Experience in data integration (ETL/ELT) development using multiple languages (e.g., Python, PySpark, SparkSQL) and data transformation (e.g., dbt) Experience building data pipelines supporting a variety of integration and information delivery methods as well as data modelling techniques and analytics Knowledge and experience with various relational databases and demonstrable proficiency in SQL and data analysis requiring complex queries, and optimization Experience with AWS-based data services technologies (e.g., Glue, RDS, Athena, etc.) and Snowflake CDW, as well as BI tools (e.g., PowerBI) Willingness to experiment and learn new approaches and technology applications Knowledge of software engineering and agile development best practices Excellent written and verbal communication skills

Skills: Bachelors degree / Master's Degree with high rankings from reputed colleges Preferably 6-8 years ETL /Data Analysis experience with a reputed firm Expertise in Big Data Managed Platform Environment like Databricks using Python/ PySpark/ SparkSQL Experience in handling large data volumes and orchestrating automated ETL/ data pipelines using CI/CD and Cloud Technologies. Experience of deploying ETL / data pipelines and workflows in cloud technologies and architecture such as Azure and Amazon Web Services will be valued Experience in Data modelling (e.g., database structure, entity relationships, UID etc.) , data profiling, data quality validation. Experience adopting software development best practices (e.g., modularization, testing, refactoring, etc.) Conduct data assessment, perform data quality checks and transform data using SQL and ETL tools Excellent written and verbal communication skills in English Self-motivated with strong sense of problem-solving, ownership and action-oriented mindset Able to cope with pressure and demonstrate a reasonable level of flexibility/adaptability Track record of strong problem-solving, requirement gathering, and leading by example Able to work well within teams across continents/time zones with a collaborative mindset

Experience: 15+ years in solution designs for data and analytics deliveries. Skills: • Experience with a range of Azure-based big data and analytics platforms like ADLS+ ADF+ DataBricks+ Azure Data Warehouse+ Power BI+ Azure Cosmo DB+ Azure ML+ etc. • Hands-on experience in the design of Near Real-time Data Processing solutions using DataBricks+ In-Stream architecture+ and modular programming. • Hands-on experience in SparkSQL+ SparkML+ PySpark+ Python • Extensive experience consulting with business; translating business use cases into data analytics specifications and designing big data solutions to deliver these use cases. • Conducting review sessions with Architecture+ Solution Design & Project Development resources as required during the Design and Development Phases. • Certifications: Certification in Designing an Azure Data Solution or relevant to Azure Architect role is mandatory. Expertise: • Solution/technical architecture in the cloud for infrastructure migration+ Big Data/analytics+ information analysis+ database management in the cloud+ IoT/event-driven/microservices in the cloud. • Experience with private public cloud architectures+ pros/cons+ and migration considerations. • Extensive hands-on experience implementing infra migration+ data migration+ and data processing using Azure services: Networking+ Windows/Linux virtual machines+ Container+ Storage+ ELB+ AutoScaling+ Azure Functions+ Serverless Architecture+ ARM Templates+ Azure SQL DB/DW+ Data Factory+ Azure Stream Analytics+ Azure Analysis Service. • DevOps on an Azure platform+ developing and deploying ETL solutions on Azure. • Strong in Power BI+ Java+ C+ Spark+ PySpark+ Unix shell/Perl scripting. • Familiarity with the technology stack available in the industry for metadata management: Data Governance+ Data Quality+ MDM+ Lineage

Role : Sr. Azure Data engineer-Data Engineer-Data platforms-Azure Total 9-12 yrs , Relevant 4+ yrs in ADB, ADF, Python- 5 yrs in Sql * are primary and Must have Data modeling * SQL Database / SQL Scripting skill * Azure Data Lake Storage (ADLS) * Azure Data Factory (ADF) * Azure Databricks * PySpark or SparkSQL * Azure Synapse ** CI/CD ** All single star are must have, Should be able to lead a team, Hands on strong tech resource

Looking for Data Architects Freelancers.Pre-sales Exp must.Hands on experience with distributed computing framework like DataBricks, Spark- Ecosystem (Spark Core, PySpark, Spark Streaming, SparkSQL)

Job Overview: We are seeking a talented and motivated Backend/Full Stack Engineer with expertise in Python and Spark to join our dynamic team. You will be responsible for developing scalable web applications, maintaining server-side functionality, and collaborating with front-end developers to ensure seamless integration. If you are passionate about building robust backends and have experience with full-stack development, wed love to meet you. Key Responsibilities: Design, implement, and maintain efficient, reusable, and reliable backend systems using Python and Spark. Proven expertise in Python programming for integration and automation. Proven expertise in Spark, SparkSQL, PySpark, Hadoop and AWS ecosystem. Experience with designing and implementing ETL processes. Create Solutions using ETL, Spark and Python and work with Engineers to create most efficient/optimize code in SparkSQL. Develop APIs (RESTful/GraphQL) and ensure responsiveness of applications. Write clean, scalable, and optimized code following best practices. Debug and troubleshoot existing systems, improving performance and scalability. Participate in the full software development lifecycle, including code reviews, testing, and deployment. Ensure the security and scalability of web applications. Work closely with product managers, designers, and other stakeholders to understand and implement business requirements. Required Skills and Qualifications: Bachelors degree in Computer Science, Information Technology, or related field (or equivalent practical experience). Strong proficiency in Spark, PySpark, SparkSQL, Python and frameworks like Django, Flask, or FastAPI. Experience with front-end technologies like HTML5, CSS3, and JavaScript (React/ Angular/ Vue.js is a plus). Solid understanding of database technologies such as PostgreSQL, MySQL, or MongoDB. Familiarity with version control tools like Git and working in an Agile environment. Experience with Docker, CI/CD pipelines, and cloud platforms (AWS, GCP, or Azure). Strong problem-solving skills and attention to detail.