Senior Data Engineer
2 weeks ago
Role : Senior Data Engineer - Cloud Analytics
Years of Experience : 5
Job Description :
As a Senior Data Engineer specializing in Cloud Analytics, you will be responsible for designing, building, and maintaining scalable data pipelines and analytics solutions on cloud platforms.
Leveraging your expertise in data engineering, cloud technologies, and analytics tools, you will play a key role in enabling data-driven decision-making and driving business insights through advanced analytics and visualization techniques.
Primary Skills : SAP Hana, SAP BODS, Azure,ADF, AWS, Glue
Secondary Skills : Tableau, Snowflake
Role Description :
Data engineering role requires creating and managing technological infrastructure of a data platform, be in-charge / involved in architecting, building, and managing data flows / pipelines and construct data storages (noSQL, SQL), tools to work with big data (Hadoop, Kafka), and integration tools to connect sources or other databases.
Role Responsibility :
- Translate functional specifications and change requests into technical specifications
Translate business requirement document, functional specification, and technical specification to related coding
Develop efficient code with unit testing and code documentation
Ensuring accuracy and integrity of data and applications through analysis, coding, documenting, testing, and problem solving
Setting up the development environment and configuration of the development tools
Communicate with all the project stakeholders on the project status
Manage, monitor, and ensure the security and privacy of data to satisfy business needs
Contribute to the automation of modules, wherever required -
- To be proficient in written, verbal and presentation communication (English)
Co-ordinating with the UAT team
Role Requirement :
- Proficient in basic and advanced SQL programming concepts (Procedures, Analytical functions etc.)
Good Knowledge and Understanding of Data warehouse concepts (Dimensional Modeling, change data capture, slowly changing dimensions etc.)
Knowledgeable in Shell / PowerShell scripting
- Knowledgeable in relational databases, nonrelational databases, data streams, and file stores
Knowledgeable in performance tuning and optimization
- Experience in Data Profiling and Data validation
- Experience in requirements gathering and documentation processes and performing unit testing
Understanding and Implementing QA and various testing process in the project
Knowledge in any BI tools will be an added advantage
- Sound aptitude, outstanding logical reasoning, and analytical skills
Willingness to learn and take initiatives
- Ability to adapt to fast-paced Agile environment
Additional Requirement :
Design and implement scalable data architectures on cloud platforms (e.g., AWS, Azure) to support analytics and business intelligence initiatives.
Define data models, schemas, and structures to optimize data storage, retrieval, and processing for analytical workloads.
Collaborate with data architects and solution architects to ensure alignment with overall data strategy and architecture principles.
Develop and maintain data integration pipelines and ETL workflows using tools such as SAP BODS, AWS Glue, Azure Data Factory (ADF), and custom Python scripts.
Provide technical support to clients for analytics systems, including ETL processes, Tableau dashboards, and cloud-based data platforms.
Good experience in SQL (SAP HANA), Tableau, AWS S3, Azure ADLS & ADF, Snowflake, and Python.
Lead the resolution of critical issues and ad-hoc requirements, ensuring timely and effective solutions.
Gather input and requirements from clients for Change Requests (CR) and projects, ensuring clear communication and understanding of client needs.
Prioritize and allocate tickets and tasks to team members based on urgency and SLAs, ensuring efficient use of resources and timely resolution of issues.
Facilitate cross-training for the team on relevant technologies to improve expertise and collaborations.
Monitor system performance and implement optimizations to enhance efficiency and scalability.
- Flag concerns, risks, or blockers to clients at the right time for CR/Project requirements, ensuring transparency and proactive management.
AI/ML knowledge is a plus.
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