Core Responsibilities of a Data Engineer in D&A
- Data Pipeline Design & Development
Data Engineers are responsible for designing and buildingrobust, scalable, and high-quality data pipelinesthat support analytics and reporting needs. This includes:
- ETL/ELT development using tools like Azure Data Factory , Databricks , and Snowflake .
- Integration of structured and unstructured data from various sources into data lakes and warehouses.
- Cloud Platform Engineering
They operationalize data solutions on cloud platforms, integrating services like,
Snowflake, and third-party technologies.
- Manage environments, performance tuning, and configuration for cloud-native data solutions.
- Data Modeling & Architecture
- Apply dimensional modeling , star schemas , and data warehousing techniques to support business intelligence and machine learning workflows.
- Collaborate with solution architects and analysts to ensure models meet business needs.
- Data Governance & Security
- Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
- Implement data masking , access controls, and metadata management for sensitive datasets.
- Collaboration & Agile Delivery
- Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.
- Participate in Agile ceremonies , sprint planning, and DevOps practices for continuous integration and deployment.
- Mentorship & Talent Development
- Help business users understand and leverage analytics tools effectively.
Key Skills Required
- Programming : Python, SQL, Spark
- Cloud Platforms : Azure, AWS, Snowflake
- Data Tools : DBT, Erwin Data Modeler, Apache Airflow
- Governance : Data masking, metadata management, SOX compliance
- Soft Skills : Communication, problem-solving, stakeholder engagement
- Experience in Data Eng > 7 years