Data Engineer

Bhasaka Technologies; Pune District, Bengaluru, Hyderabad; Hybrid; INR 15,00,000 - 25,00,000; Full time

Job summary

A leading data engineering company in India is looking for a highly experienced Senior Data Engineer to design, build, and maintain scalable data pipelines. The ideal candidate will have strong expertise in PySpark, 5+ years of experience in data engineering, and proficiency in SQL and Python. This role involves collaborating with various teams to ensure data quality and governance.

Qualifications

• 5+ years of experience in data engineering roles.
• Strong hands-on experience with PySpark for data transformation and processing.
• Deep understanding of distributed computing concepts, data partitioning, and performance tuning.

Responsibilities

• Design, implement, and maintain scalable ETL/ELT pipelines using PySpark.
• Collaborate closely with data scientists, analysts, and business stakeholders.
• Optimize PySpark jobs for distributed environments.

Skills

PySpark

SQL

Python

Distributed computing concepts

Data engineering

Tools

Apache Spark

Hadoop

Delta Lake

Apache Airflow

Job description

Senior Data Engineer --- PySpark

Location: Pune / PAN India
Job Type: Full-time
Experience: 5+ years

Job Summary

We are looking for a highly experienced Senior Data Engineer with strong expertise in PySpark and large-scale data processing to join our data engineering team. In this role, you will be responsible for designing, building, and maintaining advanced data pipelines that support enterprise-level analytics and data science initiatives.

Key Responsibilities

• Design, implement, and maintain scalable and efficient ETL/ELT pipelines using PySpark.
• Work with big data frameworks such as Apache Spark, Hadoop, Hive, and Delta Lake.
• Handle large volumes of structured and unstructured data across various sources (databases, APIs, flat files, etc.).
• Develop and optimize complex data transformation workflows and batch/streaming jobs.
• Ensure data quality, integrity, and governance throughout the data lifecycle.
• Collaborate closely with data scientists, analysts, DevOps, and business stakeholders.
• Troubleshoot performance issues and optimize PySpark jobs for distributed environments.
• Manage workflows using orchestration tools such as Apache Airflow or similar.
• Contribute to the architecture and design of scalable, fault-tolerant data platforms.

Required Skills & Qualifications

• 5+ years of experience in data engineering roles.
• Strong hands-on experience with PySpark for data transformation and processing.
• Proficient in SQL and Python.
• Deep understanding of distributed computing concepts, data partitioning, and performance tuning.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with data lakehouse architectures (e.g., Delta Lake, Databricks).
• Knowledge of version control (Git), CI/CD, and agile methodologies.

Nice to Have

• Exposure to streaming data technologies like Kafka, Spark Streaming, or Flink.
• Experience with Snowflake, Redshift, or BigQuery.
• Knowledge of data governance, data lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with containerization (Docker, Kubernetes).

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