Senior Data Engineer

Dentsu Global Services; Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Merkle in Mumbai (DGS India) is seeking a Senior Data Engineer with 5 years of hands-on experience to build robust data pipelines and analytics infrastructure using Databricks and SQL. You will drive data-focused initiatives, work closely with cross-functional teams, and ensure scalable, cloud-native data solutions.

The role emphasizes Databricks, Spark SQL, PySpark, Python scripting, and cloud ETL tools such as Azure Data Factory or AWS Glue, with a focus on data quality, monitoring, and

Qualifications

• 5+ years of experience in data engineering, ETL development, or data analytics engineering.
• Strong proficiency in Databricks (Spark SQL, PySpark) with pipeline development experience.
• Solid SQL skills including optimization, joins, aggregations, and window functions.
• Hands-on Python for data processing and scripting.
• Experience with cloud ETL services like Azure Data Factory or AWS Glue.

Responsibilities

• Develop and deploy ETL/ELT pipelines using Databricks, PySpark, and SQL.
• Write clean SQL and Python code for data processing and analytics.
• Monitor job executions and troubleshoot data quality issues within SLA timelines.
• Collaborate with Senior Engineers, Data Scientists, and Analytics teams to deliver solutions.
• Implement data validation, error handling, and logging for pipeline reliability.
• Document code, architecture decisions, and runbooks for operations.
• Participate in code reviews and knowledge sharing.

Skills

Databricks

SQL

Python

Cloud ETL

Data Modeling

Tools

Azure Data Factory

AWS Glue

Job description

Job Descriptions

Data Engineering Roles | Databricks & SQL Focus

Job Description

Data Engineering Roles | Databricks & SQL Focus

SENIOR DATA ENGINEER (5 Years Experience)

Position Overview

We 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

Required Skills & Experience

• 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

Required Certifications (Nice to Have)

• Databricks Certified Data Engineer (Associate) OR
• Snowflake SnowPro Core Certified OR
• AWS Certified Data Engineer (Associate) OR equivalent professional data engineering certification

Preferred Qualifications

• 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 Park

Brand

Merkle

Time Type

Full time

Contract Type

Consultant#DGS