Senior Data Engineer

ADA; Bengaluru; Presencial; INR 1.500.000 - 3.000.000; Jornada completa

Descripción de la vacante

ADA is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and analytics infrastructure for global enterprise clients. You will work with cross-functional teams to turn raw data into actionable assets, leveraging PySpark, SQL, and modern data tools.

The role emphasizes problem-solving, client communication, and the ability to adapt to diverse tech stacks across on-prem and cloud environments.

Formación

• 2–4 years hands-on software/data engineering experience, preferably in client-facing/IT services.
• Strong SQL (complex queries, performance tuning) and Python skills.
• Practical experience with Apache Spark (PySpark) for distributed processing.
• Solid understanding of data warehousing concepts, ETL/ELT architecture, and orchestration tools like Airflow.

Responsabilidades

• Design, build, and optimize ETL/ELT data pipelines.
• Implement and manage data solutions on at least one major cloud platform (AWS, GCP, or Azure).
• Architect efficient data models for data lakes, warehouses, and reporting layers.
• Monitor, troubleshoot, and optimize pipelines and queries for performance and cost.
• Collaborate with client teams to gather requirements and deliver robust data solutions.

Conocimientos

SQL

Python

PySpark

Data modeling

Airflow

Herramientas

dbt

Snowflake

Docker

Kubernetes

Kafka

Descripción del empleo

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:
• 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).

We transform businesses using data, AI and tech | ADA

Pioneers in data and analytics, we are powering global marketing and commerce digital transformation with data and AI-led impact. Learn more here!