Build and maintain scalable ETL/ELT pipelines and data platforms, optimize queries and databases, design analytics-ready data models, ensure data quality and governance, collaborate with stakeholders, and support data products and automation for business intelligence and analytics.
Job Summary & Responsibilities
We are seeking skilled Senior Data Engineers to build, and maintain scalable platforms and pipelines that power analytics, reporting, and data products across the organization. You will develop robust ETL/ELT solutions, optimize data workflows, and enable trusted, high-quality data for business intelligence, advanced analytics, and data-driven decision-making. You will translate business requirements into robust database logic, automated data workflows, and insightful dashboards that enable data-driven decision-making across the organization. Depending on experience level, the role will contribute to solution design, development, optimization, and technical leadership within the data services team.
Roles and Responsibilities
- Build, optimize, and manage data ingestion workflows from multiple structured and unstructured data sources.
- Develop and optimize SQL queries, stored procedures, functions, and views for high-volume relational databases.
- Design and maintain data models that support analytics, reporting, and data products.
- Design, develop, and maintain scalable data pipelines using SQL, Python, and modern ETL/ELT frameworks.
- Perform data profiling, cleansing, validation, and quality monitoring to ensure data accuracy, integrity, and consistency.
- Optimize database and pipeline performance through indexing, partitioning, query tuning, and workload optimization.
- Collaborate with Product Managers, and business stakeholders to understand business requirements and deliver analytics-ready data solutions.
- Support the development and enhancement of data products by delivering reliable, scalable, and governed datasets.
- Document data pipelines, data models, technical designs, and operational processes in accordance with data governance standards.
- Implement best practices for data security, governance, metadata management, and compliance.
- Contribute to automation, reusable frameworks, and continuous improvement initiatives.
Qualifications & Experience
- Bachelor's degree in computer science, Information Technology, and Engineering.
- 6 - 10 years of strong hands-on experience in SQL development, ETL, and BI/reporting.
Required Skills & Experience
- Strong proficiency in SQL (T-SQL / PL-SQL) with advanced query writing and performance tuning.
- Hands-on experience with ETL/ELT tools such as SSIS, Azure Data Factory, Fivetran, AWS Glue
- Experience with Azure Data Services, such as: Azure Data Factory, Azure Synapse Azure Data Lake Storage (ADLS), Azure SQL Database, Microsoft Fabric.
- Hands-on experience with AWS Data Services including AWS Lambda, S3, Athena, Lake Formation & DataZone.
- Strong programming skills in Python for data engineering and automation.
- Strong data analysis skills, including data exploration, profiling, validation, KPI development, and translating business requirements into actionable insights.
- Solid understanding of data warehousing concepts, star/snowflake schemas, and dimensional modeling.
- Experience supporting or developing data products and understanding the end-to-end data product lifecycle.
Preferred Skills:
- Familiarity with version control (Git) and CI/CD for data pipelines.
- Exposure to Power BI, Service administration, gateways, and workspace management.
- Understanding of data privacy, retention, and governance frameworks.
Competencies:
- Strong communication and stakeholder management skills.
- Ability to work both independently and collaboratively in a hybrid.
- Attention to detail and commitment to data accuracy.
- Adaptability and eagerness to learn new tools and technologies.
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