Job highlights

- Performance Tuning: Monitor,troubleshoot,and optimize data pipelines and queries for maximum performance and cost-efficiency
- Required Skills Qualifications .
- Experience: 2 to 4 years of hands-on software / data engineering experience,preferably within a client-facing or IT services environment
- Experience with modern data stack tools (dbt,Snowflake)

We are looking for a driven and technically sharp Senior Data Engineer to join our growing data practice. In this role, you will design, build, and maintain scalable data pipelines, data warehouses, and analytics infrastructure for our global enterprise clients. As a services company, we value strong problem-solving skills, client communication, and the ability to rapidly adapt to diverse technology stacks. You will work closely with client stakeholders, data scientists, and analytics teams to turn raw data into high-value, actionable assets.

Key Responsibilities

Pipeline Development: Design, build, and optimize robust ETL/ELT data pipelines using Python, SQL, and Apache Spark to process large volumes of structured and unstructured data.

Cloud Infrastructure: Implement and manage data solutions on at least one major cloud platform (AWS, GCP, or Azure).

Data Modeling: Architect efficient data models (dimensional modeling, star/snowflake schemas) for data lakes, data warehouses, and reporting layers.

Performance Tuning: Monitor, troubleshoot, and optimize data pipelines and queries for maximum performance and cost-efficiency.





Collaboration Delivery: Work directly with cross-functional and client-facing teams to gather requirements, deliver robust data solutions, and follow best engineering practices (CI/CD, version control, testing).

Required Skills Qualifications

Experience: 2 to 4 years of hands-on software/data engineering experience, preferably within a client-facing or IT services environment.

Core Languages: Advanced proficiency in SQL (complex queries, performance tuning) and Python (scripting, data manipulation libraries).

Data Frameworks: Solid practical experience with Apache Spark (PySpark) for distributed data processing.

Cloud Platforms: Hands-on implementation experience with any one cloud ecosystem:

AWS (S3, Glue, EMR, Redshift, Athena)

GCP (BigQuery, Dataflow, Dataproc, GCS)

Azure (Azure Data Factory, Databricks, Synapse Analytics)

Data Concepts: Solid understanding of data warehousing concepts, ETL/ELT architecture, workflow orchestration tools (e.g., Apache Airflow), and data governance.

Good-to-Have Skills

Experience with modern data stack tools (dbt, Snowflake).

Containerization and orchestration tools like Docker and Kubernetes.

Exposure to streaming data technologies (Kafka, Spark Streaming).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Data Engineer (Bengaluru)
🏢 ADA Global
📍 Bengaluru