Data Engineer

This role is for one of the Weekday's clients

Min Experience: 4 years

Location: India

JobType: full-time

We are seeking an experienced Data Engineer with strong expertise in Databricks and modern data engineering practices. The ideal candidate will have 4+ years of hands-on experience in developing scalable data pipelines, managing distributed data systems, and supporting end-to-end CI/CD processes. This role involves architecting and optimizing data workflows that enable seamless data-driven decision-making across the organization.

Requirements

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for large-scale datasets using Spark, Hive, or Glue.
• Develop and optimize data integration workflows using ETL tools such as Informatica, Talend, or SSIS.
• Write, optimize, and maintain complex SQL queries for data transformation and analytics.
• Collaborate with cross-functional teams including data scientists, analysts, and product stakeholders to translate requirements into technical solutions.
• Deploy data workflows using CI/CD pipelines and ensure smooth automated releases.
• Monitor and optimize data workflows for performance, scalability, and reliability.
• Ensure data accuracy, governance, security, and compliance across pipelines.
• Work with cloud-based data platforms such as Azure (ADF, Synapse, Databricks) or AWS (EMR, Glue, S3, Athena).
• Maintain clear documentation of data systems, architectures, and processes.
• Provide mentorship and technical guidance to junior team members.
• Stay current with emerging data engineering tools, technologies, and best practices.

What You’ll Bring

• Bachelor’s degree in IT, Computer Science, or related field.
• 4+ years of experience in data engineering and distributed data processing.
• Strong hands-on experience with Databricks or equivalent technologies (Spark, EMR, Hadoop).
• Proficiency in Python or Scala.
• Experience with modern data warehouses (Snowflake, Redshift, Oracle).
• Solid understanding of distributed storage systems (HDFS, ADLS, S3) and formats such as Parquet and ORC.
• Familiarity with orchestration tools such as ADF, Airflow, or Step Functions.
• Databricks Data Engineering Professional certification (preferred / required as needed).
• Experience in multi-cloud or migration-based projects is a plus.