Senior Data Engineer - Python, SQL & AI-Augmented Engineering

Michael Page; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Benefits offered by this job

Cosmetics industry exposure

AI-augmented engineering environment

Hyderabad-based role

Job summary

Michael Page in Hyderabad is seeking a hands-on Senior Data Engineer to join our data squad and drive the build phase of the data strategy. You will work with the Tech Lead to deliver production-grade pipelines and optimize SQL.

The role emphasizes AI-assisted development, Airflow DAGs, ETL/Reverse ETL pipelines, and data activation with tools like BigQuery, Dataform, and Google Cloud Dataflow. You will mentor juniors, balance code quality with business deadlines, and contribute to CI/CD for

Qualifications

• 6+ years in Data Engineering.
• Experience with AI tooling and Python/SQL.
• Hands-on with Airflow, BigQuery and data pipelines.
• Ability to translate architecture into optimized tables and views.

Responsibilities

• Build, test and maintain production-grade data pipelines and ETL/Reverse ETL processes.
• Develop and optimize SQL queries and data transformations for performance.
• Collaborate with Tech Lead to implement the data strategy and CI/CD for data workflows.
• Mentor junior engineers and ensure code quality with AI-assisted development.

Skills

Python

Advanced SQL

ETL/ELT design

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

Airflow

BigQuery

Dataform

Google Cloud Dataflow (Apache Beam)

Apache Spark

Git

dbt

Job description

• Be a part of growing Tech / GCC in Hyderabad
• European based the Cosmetic Industry

About Our Client

This company operates in the cosmetics sector, part of the broader FMCG industry, and is based in Hyderabad.

Job Description

We are looking for a hands-on Senior Data Engineer to join our data squad and work directly with the Technical Lead to execute our data strategy. You will be responsible for the "build" part of the blueprint. This role focuses on delivering production-grade implementations, optimizing complex SQL, and building scalable ETL/Reverse ETL pipelines using Python, SQL, Airflow and Apache Beam. You will collaborate with the Tech Lead to ensure that AI coding assistants are used effectively, code is clean, and data is activated reliably via automated piplines.
In this role, You will..
1. AI-Driven Data Engineering (Execution Focus)
* AI Productivity: Use GitHub Copilot, Cursor, ChatGPT or Claude Code to generate complex SQL transformations, Python scripts, PySpark logic and data processing pipelines, in accordance with the AI standardization strategy.
* Performance Tuning: Use AI tools to analyze query execution plans, identify bottlenecks, and refactor legacy SQL for performance and cost efficiency (e.g., reducing BigQuery/Snowflake slot usage).
* Data Validation: Utilize AI to generate comprehensive test suites for data quality checks and schema drift detection.
ETL & Reverse ETL Build
* Orchestration: Build and maintain complex, robust and idempotent Airflow DAGs. Ensure high availability and observability of schedules.
* Batch & Streaming: Develop data pipelines using Python, Spark, or Google Cloud Dataflow (Apache Beam), Dataform to handle large-scale data transformations.
* Data Activation: Design and implement Reverse ETL processes to sync data between the Data Warehouse and critical business applications (Salesforce, Tealium, Braze, Google Ads etc), ensuring "Data Activation" is seamless and reliable.
3. Python & SQL Excellence
* Core Libraries: Contribute to the development and maintenance of internal Python libraries and custom Airflow operators to ensure DRY (Don’t Repeat Yourself) principles across the team.
* SQL Governance: Write high-performance SQL code. Conduct peer reviews focused on window functions, partitioning, and indexing to maintain the "Gold Standard" set by the Tech Lead.
4. Collaboration with Tech Lead & Architecture
* Blueprint Execution: Work closely with the Tech Lead to translate the Solution Architect's high-level ERDs (Entity Relationship Diagram) into optimized physical tables and views.
* Operational Integrity: Refine the CI/CD strategy for data (Git, dbt, or similar) alongside the Tech Lead and DevOps to ensure smooth, zero-downtime deployments from development to production.

The Successful Applicant

We’re looking for someone who has:

• AI Tooling: Proven experience utilizing AI coding assistants (GitHub Copilot, Claude Code, Cursor) to accelerate development and troubleshooting.
• Data Stack: Expert-level proficiency in Python 3.x (data-focused libraries) and advanced SQL (analytical functions, recursive CTEs, query optimization), BigQuery and Dataform are a plus.
• Orchestration: 3+ years of hands-on experience with Apache Airflow (DAG development, operators, sensors).
• Cloud Processing: Strong experience with Google Cloud Dataflow (Apache Beam), Dataproc, Spark, or similar cloud-native processing frameworks.
• Data Concepts: Deep understanding of ELT/ETL patterns, Data Lakehouse architecture, and Reverse ETL strategy.

Experience: 6+ years in Data Engineering.

• Mentorship: Experience mentoring junior engineers, providing constructive code reviews, and fostering a collaborative team environment.
• Pragmatism: An ability to balance code perfection with business deadlines using AI.
• Collaboration: Excellent communication skills to clearly articulate technical trade-offs to the Tech Lead and stakeholders.
• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).

What's on Offer

• Opportunity to work in the FMCG industry, specifically in the cosmetics sector
• Engaging role at the intersection of technology and AI-augmented engineering
• Collaborative working environment in Hyderabad