Project Role : Data Engineer

Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

Data Engineering

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

As a Data Engineer, a typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. This role requires creating efficient data pipelines and ensuring the seamless migration and deployment of data across various systems. The position demands continuous attention to data quality and the implementation of processes that facilitate smooth data flow and accessibility, contributing to the overall data infrastructure and operational success.

Provide solutions to problems for their immediate team and across multiple teams.

Lead the design and implementation of scalable data architectures to support business needs.

Coordinate cross-functional efforts to optimize data workflows and improve system performance.

strong hands-on expertise in Databricks, Python, PySpark, and SQL. The ideal candidate will have a proven track record of designing and building scalable, production-grade data pipelines and must have solid hands-on experience implementing Medallion Architecture across Bronze, Silver, and Gold layers.

This role offers the prospect to work with modern cloud platforms, contribute to enterprise data governance practices, and engage with emerging AI and GenAI technologies.

Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Python, and SQL.



Build and manage ETL/ELT pipelines for batch and large-scale data processing. Implement and maintain Medallion Architecture as a core data structuring standard. Develop data transformation frameworks, optimize Spark workloads for performance and cost efficiency, and implement data quality checks and monitoring. Collaborate cross-functionally to translate business requirements into scalable solutions, troubleshoot production pipelines, and partner with data architects to deliver enterprise-grade data solutions.

Databricks Python PySpark SQL Medallion Architecture (Bronze / Silver / Gold)

4–6 years of production Data Engineering experience. Deep understanding of ETL/ELT design patterns and large-scale data processing.

Cloud: Microsoft Azure (ADF, ADLS, Synapse) GCP (BigQuery, GCS, Dataflow)

Data Governance Delta Lake Lakehouse Architecture Data Lineage Metadata Management

Bonus / Plus Skills

AI Generative AI (GenAI) Large Language Models (LLMs) Agentic AI Canonical Data Models AI–Data Platform Integration

Ability to design and deliver maintainable, scalable data solutions independently. Eagerness to learn and work with emerging technologies across Data Engineering, AI, and GenAI.

Must To Have Skills: Proficiency in Data Engineering.

Experience with building and managing data pipelines and ETL processes.

Solid knowledge of data storage solutions and database management.

Familiarity with cloud-based data platforms and distributed computing frameworks.

Ability to ensure data quality through validation and monitoring techniques.

Competence in scripting and programming languages relevant to data processing.

The candidate should have minimum 5 years of experience in Data Engineering.

This position is based at our Hyderabad office.

A 15 years full time education is required.

📌 Data Engineers required ASAP (Secunderabad)
🏢 Accenture
📍 Secunderabad