Design, build, and maintain scalable ETL/ELT pipelines and data models using SQL and Python. Optimize database and pipeline performance, enforce data quality and governance, and collaborate with stakeholders to deliver analytics-ready datasets and data products.
Job Summary & Responsibilities
We are seeking skilled 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.
- 4--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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