Senior Data Engineer

dentsu

Mumbai City

On-site

INR 1,800,000 - 2,500,000

Full time

8 days ago

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Job summary

Merkle India is seeking a Senior Data Engineer with 5 years of hands-on experience to build and maintain robust data pipelines using Databricks and SQL in a cloud-native environment at our Mumbai office.

You will implement ETL/ELT pipelines, write PySpark and Python code, ensure data quality, collaborate with data science and analytics teams, and contribute to platform initiatives across Azure/AWS ecosystems.

Qualifications

  • 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.

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.

Skills

5+ years experience in data eng
Databricks PySpark
SQL
Python
Azure/AWS data tools
Data architecture and modeling
Data quality & validation

Tools

Apache Airflow
Git & CI/CD
Snowflake/Redshift
BigQuery

Job description

Job Description:

JOB DESCRIPTIONS

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

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