Overview

We have an urgent requirement for a Data Engineer with 4–7 years of experience for an onsite role based at our office in Aundh, Pune.

• Role: Data Engineer
• Experience: 4–7 Years
• Open Positions: 5 (2 remote)
• Location: Aundh, Pune (most preferred), Remote
• Work Mode: Onsite (preferred) and Remote (Note: Onsite would be more preferable and will be given first chance.)
• Joining Preference: Immediate / Early Joiners Preferred

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python and PySpark.
• Write and optimize complex SQL queries, stored procedures, and database objects.
• Build and maintain cloud-based data pipelines using AWS or Azure data services.
• Ingest, transform, and integrate structured and semi-structured data from multiple data sources.
• Perform data transformation, cleansing, validation, and integration.
• Build and maintain efficient data models for analytics and reporting.
• Monitor data pipelines and troubleshoot performance, reliability, and data quality issues.
• Optimize data processing jobs for scalability and performance.
• Collaborate with Data Analysts, BI developers, Software Engineers, and other cross-functional teams.
• Ensure data quality, reliability, security, and governance across data platforms.
• Follow best practices for code quality, testing, documentation, version control, and CI/CD.

Required Skills

• Strong programming skills in Python.
• Strong hands-on experience with SQL, including joins, CTEs, window functions, query optimization, and performance tuning.
• Hands-on experience with PySpark / Apache Spark for large-scale data processing.
• Strong understanding of ETL/ELT concepts and data integration.
• Experience working with cloud platforms such as AWS or Azure.
• Experience with cloud-based data engineering, ETL, and big data technologies.
• Good understanding of data warehousing and data modeling concepts.
• Experience working with relational databases and large datasets.
• Understanding of batch and distributed data processing.
• Experience with workflow orchestration tools such as Apache Airflow or similar.
• Familiarity with Git, CI/CD, and software development best practices.

Preferred Skills

• Knowledge of data lakes, lakehouse, and modern data warehouse architectures.
• Experience working with structured and semi-structured data from multiple sources.
• Experience implementing data validation, monitoring, and pipeline optimization.
• Exposure to big data technologies such as Spark, Hive, or similar frameworks.
• Experience working in Agile/Scrum development environments.

Other Details

We are hiring under the following engagement models:

• Permanent Hiring: The candidate sourced by your organization will be hired directly by us. A one-time placement fee will be applicable. The commercial terms can be discussed mutually.
• Contract Engagement: Initial contract duration of 3 months. There is a high possibility of extension to 6 months or longer, based on project requirements and performance.

Interview Process (Applicable to Both Models):

• L1 Technical Round
• L2 Technical Round
• Client Round (only if required after CV review; otherwise, we may proceed directly with onboarding)