Data Engineer

Data Engineer
📍 Location: Bangalore
🏢 Work Mode: Hybrid – 3 days/week from office
Type: Contractual role
💼 Experience: 8+ Years
About the Role
We are looking for an experienced Data Engineer to design, build, and maintain scalable data solutions and pipelines. The ideal candidate will have strong hands-on experience in data engineering, cloud platforms, ETL/ELT processes, and modern data technologies, with the ability to work closely with analytics, technology, and business teams.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
Build and optimize data ingestion, transformation, and processing frameworks.
Develop robust data solutions to support analytics, reporting, and business intelligence requirements.
Work with large and complex datasets to ensure data quality, accuracy, and reliability.
Design and maintain data models, data warehouses, and data lakes.
Optimize data pipelines and queries for performance and scalability.
Implement data validation, monitoring, and quality checks.
Collaborate with Data Scientists, BI Developers, Architects, and business stakeholders.
Troubleshoot data pipeline failures and resolve production issues.
Follow best practices around data security, governance, documentation, and engineering standards.
Contribute to cloud-based data platform architecture and modernization initiatives.
Mandatory Skills
8+ years of experience in Data Engineering or related roles.
Strong programming experience in Python and/or Java/Scala.
Strong hands-on experience with SQL and relational databases.
Experience developing ETL/ELT pipelines and data processing workflows.
Strong understanding of Data Warehousing, Data Lakes, and Data Modeling.
Experience with distributed data processing technologies such as Apache Spark.
Experience working with cloud platforms such as AWS, Azure, or GCP.
Good understanding of data integration and orchestration tools.
Experience with Git, CI/CD, and Agile development practices.
Strong analytical and problem-solving skills.
Good to Have
Experience with Databricks, Snowflake, or BigQuery.
Knowledge of Apache Kafka or other streaming technologies.
Experience with Airflow or similar workflow orchestration tools.
Exposure to Docker/Kubernetes.
Understanding of data governance and security frameworks.
Experience working with real-time/streaming data pipelines.
Exposure to modern Lakehouse architecture.
Key Competencies
Strong ownership and problem-solving mindset.
Ability to design scalable and reliable data solutions.
Good communication and stakeholder-management skills.
Ability to work independently as well as collaboratively in a cross-functional environment.
Strong focus on data quality, performance, and engineering best practices.

Work arrangement
No