The role
Job description
Exp- 8 to 11 years
Work Mode- Remote
Role Overview
We are looking for an experienced Data Engineer with strong expertise in ETL development, Python, PySpark, Databricks, and data analytics. The candidate will be responsible for designing, developing, and optimizing scalable data pipelines to support business intelligence, analytics, and data-driven applications.
Key Responsibilities
Design, develop, and maintain ETL/ELT pipelines for data extraction, transformation, and loading.
Develop data processing solutions using Python and PySpark.
Work with Databricks to build, process, and optimize large-scale datasets.
Perform data cleaning, transformation, validation, and integration from multiple sources.
Support analytics and reporting requirements by preparing high-quality, reliable datasets.
Optimize data pipelines and Spark jobs for performance, scalability, and cost efficiency.
Work with structured and semi-structured data across different data sources.
Implement data quality checks, error handling, and monitoring.
Collaborate with data analysts, data scientists, and business teams to deliver data solutions.
Troubleshoot data pipeline issues and ensure data accuracy and consistency.Required Skills
Strong experience in ETL development.
Experience in Data Analytics.
Hands-on experience with Databricks.
Strong programming skills in Python.
Hands-on experience with PySpark.
Preferred Skills
Experience with cloud platforms such as AWS, Azure, or GCP.
Knowledge of Delta Lake and Lakehouse architecture.
Experience with orchestration tools such as Apache Airflow or Azure Data Factory.
Familiarity with BI tools such as Power BI or Tableau.
Exposure to big data processing and cloud-based data platforms