Senior Data Engineer

About ADA
ADA is the Data and AI Experience Company. We work with global enterprises to build data and AI powered experiences where every decision runs on real-time intelligence and every interaction earns trust. That's how businesses scale, stay ahead, and deliver measurable outcomes.

Our mission is ambitious: to create the world’s most intelligent growth platform for every client we serve. With over 1500+ customers across Retail, Food and Beverage, CPG, Telecommunications, Financial Services, Healthcare and Automotive, we operate in 35 markets around the world.

About the Role

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: Strong 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).

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Unfortunately, we are only able to contact shortlisted applicants. We encourage you to continuously visit our website www.adaglobal.com for regular updates on available roles

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