Develop and maintain ETL/ELT pipelines and analytics infrastructure using Databricks, PySpark, SQL, and Python. Responsibilities include data ingestion, transformation, validation, monitoring, troubleshooting, error handling, documentation, code reviews, and collaboration with engineering, data science, and analytics teams. The role also supports cloud-native data solutions, data quality, architecture, and operational reliability.
Job Description:
JOB DESCRIPTIONSData Engineering Roles | Databricks & SQL Focus
SENIOR DATA ENGINEER (5 Years Experience)Position OverviewWe are seeking a Data Engineer with 5 years of experience to develop and maintain robust data pipelines and analytics infrastructure. This role focuses on hands-on implementation using Databricks and SQL, contributing to data platform initiatives while continuously growing technical expertise in cloud-native data solutions.
Key Responsibilities- Develop and deploy ETL/ELT pipelines using Databricks, PySpark, and SQL for data ingestion, transformation, and loading
- Write clean, efficient SQL and Python code for data processing, validation, and analytics
- Support data pipeline maintenance, monitor job executions, and troubleshoot data quality issues within SLA timelines
- Collaborate with Senior Engineers, Data Scientists, and Analytics teams to understand requirements and deliver solutions
- Implement data validation, error handling, and logging mechanisms to ensure pipeline reliability
- Document code, architecture decisions, and runbooks for operational excellence
- Participate in code reviews and contribute to knowledge sharing within the engineering team
- 5+ years of professional experience in data engineering, ETL development, or data analytics engineering
- Strong proficiency in Databricks (Spark SQL, PySpark) with real-world pipeline development experience
- Solid SQL skills including query optimization, joins, aggregations, and window functions
- Hands-on experience with Python for data processing and scripting
- Experience with cloud platforms such as Azure Data Factory, AWS Glue, or similar ETL services
- Understanding of data architecture, data modeling, and relational databases
- Strong problem-solving skills with attention to data quality and accuracy
- Databricks Certified Data Engineer (Associate) OR
- Snowflake SnowPro Core Certified OR
- AWS Certified Data Engineer (Associate) OR equivalent professional data engineering certification
- Experience with orchestration tools (Apache Airflow, Tidal, Control-M, etc.)
- Familiarity with cloud data warehousing (Snowflake, Redshift, BigQuery)
- Experience with Git, CI/CD pipelines, and version control
- Knowledge of Agile methodologies and experience working in cross-functional teams
- Background in data validation frameworks and data quality testing
Location:
DGS India - Mumbai - Thane Ashar IT ParkBrand:
MerkleTime Type:
Full timeContract Type:
Consultantdentsu Mumbai, Maharashtra, IND Office
Mumbai, India
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