Data Engineer – Python / PySpark | 3-10 yr Experience

Job Description

Job Title : Data Engineer – Python / PySpark

Experience : 3 to 10 years

Number of Position : 4

Location : Pune (Client - USA)

Work Model : Full-time,  hybrid work, 3 days / week in office(Client location.)

Job Type : Contract-to-Hire

Client Domain : Utilities / Energy

About the Role

We are seeking a highly skilled Data Engineer with hands-on expertise in Python, PySpark, and Palantir Foundry. The ideal candidate will have experience working on large-scale data processing, transformation, and analytics solutions within the utilities or related domains. You will collaborate closely with business stakeholders, solution architects, and data analysts to design and deliver efficient, scalable, and high-quality data pipelines.

Key Responsibilities

Design, build, and maintain scalable ETL pipelines using Python and PySpark.

Ensure data quality, reliability, and governance across systems and pipelines.

Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

Perform performance tuning and troubleshooting of big data applications.

Work with large datasets from multiple sources (structured / unstructured) and prepare them for analytics and reporting.

Follow best practices in coding, testing, and deployment for enterprise-grade data applications.

Requirements Required Skills & Qualifications

3–10 years of professional experience in data engineering, preferably in utility, energy, or similar industries.

Strong proficiency in Python programming.

Hands-on experience with PySpark for big data processing.

Good understanding and working knowledge of Palantir Foundry (pipelines, ontology, data modeling, transforms, code repositories,data integration and transformation).

Experience with SQL and handling large datasets.

Familiarity with data governance, data security, and compliance requirements in enterprise environments.

Strong problem-solving and analytical skills.

Excellent communication and collaboration skills.

Nice-to-Have Skills

Experience with AWS , Azure , or GCP cloud data services.

Knowledge of utilities domain data models and workflows.

Exposure to DevOps / CI-CD pipelines for data engineering solutions.

Knowledge of visualization tools like Tableau , Power BI , or Palantir dashboards.

Experience in Palantir Foundry.

Benefits Why Join Us

Work on cutting-edge Palantir Foundry-based solutions in the utilities sector.

Be part of a dynamic, collaborative, and innovation-driven team.

Opportunity to grow your technical expertise across modern data platforms.

Requirements

Required Skills & Qualifications 3–10 years of professional experience in data engineering, preferably in utility, energy, or similar industries. Strong proficiency in Python programming. Hands-on experience with PySpark for big data processing. Good understanding and working knowledge of Palantir Foundry (pipelines, ontology, data modeling, transforms, code repositories,data integration and transformation). Experience with SQL and handling large datasets. Familiarity with data governance, data security, and compliance requirements in enterprise environments. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Nice-to-Have Skills Experience with AWS, Azure, or GCP cloud data services. Knowledge of utilities domain data models and workflows. Exposure to DevOps / CI-CD pipelines for data engineering solutions. Knowledge of visualization tools like Tableau, Power BI, or Palantir dashboards. Experience in Palantir Foundry.