Data Engineer
Posted Updated
Description
RoleOverview
Weare looking for a hands-on Data Engineer to design, build, and optimizescalable data pipelines on the Databricks Lakehouse platform. The role involvescollaborating with analysts, data scientists, and business teams to deliverreliable, analytics-ready data assets.
KeyResponsibilities
- Build and maintain batch and streaming data pipelines using PySpark and Databricks.
- Implement medallion architecture (Bronze, Silver, and Gold layers).
- Optimize Spark jobs for performance and cost efficiency.
- Ensure data quality, lineage, and governance using Unity Catalog and automated validation.
- Integrate data from APIs, databases, files, and event streams.
- Implement CI/CD, version control, and workflow orchestration.
- Monitor, troubleshoot, and document data pipelines and data models.
- Collaborate with stakeholders to translate business requirements into technical solutions.
RequiredQualifications
- 3–5 years of hands-on data engineering experience.
- Strong PySpark skills, including DataFrames, Spark SQL, UDFs, and performance tuning.
- Proven experience building production pipelines on Databricks.
- Working knowledge of Delta Lake, including ACID transactions, time travel, merge/upsert, and schema evolution.
- Advanced SQL and strong Python programming skills.
- Experience with Azure, AWS, or GCP cloud platforms.
- Understanding of data modelling, Lakehouse architecture, and ETL/ELT patterns.
- Familiarity with Git and CI/CD practices.
PreferredQualifications
- Databricks Data Engineer Associate or Professional certification.
- Experience with Unity Catalog, Auto Loader, and Structured Streaming.
- Familiarity with Airflow, Azure Data Factory, or Databricks Workflows.
- Knowledge of Terraform and testing frameworks such as pytest.
- Exposure to Kafka, Event Hubs, dbt, or MLOps workflows.
- Experience working in regulated or enterprise environments.
KeySkills
- PySpark and Python
- Databricks and Delta Lake
- Advanced SQL
- Data Pipeline Development
- Medallion Architecture
- Cloud Data Engineering
- Data Quality and Governance
- CI/CD and Git
- Spark Performance Tuning
DesiredAttributes
- Strong problem-solving and debugging skills.
EA Number: 11C4879
Skills
- Airflow
- Analytics
- API
- AWS
- Azure
- Azure Data Factory
- CI/CD
- Cloud
- Data Engineering
- Data Modeling
- Data Pipelines
- Data Quality
- Databricks
- dbt
- Delta Lake
- ELT
- ETL
- GCP
- Git
- Kafka
- Lakehouse
- Medallion Architecture
- MLOps
- PySpark
- pytest
- Python
- Spark
- SQL
- Terraform
- Unity
- Unity Catalog
- Version Control
- Workflow Orchestration