Data Engineer

TymblHub; Hyderabad; On-site; INR 3,000,000 - 4,500,000; Full time

Job summary

EPAM Systems in Hyderabad is hiring Senior/Lead Data Engineers with strong expertise in Spark, Python, and cloud platforms (AWS or GCP). You will design, build, and optimize large-scale data pipelines and data lakes for global clients.

Responsibilities include implementing Apache Spark jobs, developing PySpark workflows, and leveraging Databricks for Delta Lake and Lakehouse architectures while ensuring data quality, security, and governance across pipelines. Immediate joiners preferred.

Qualifications

• 6 to 15 years of relevant Big Data Engineering experience.
• Strong PySpark and SQL skills.
• Hands-on experience with cloud platforms (AWS or GCP) and Databricks.

Responsibilities

• Design and implement large-scale data ingestion and processing pipelines using Apache Spark and Python.
• Build and maintain data workflows on AWS or GCP cloud environments.
• Utilize Databricks for collaborative data engineering, data science, and pipeline optimization (Delta Lake, Lakehouse architecture).
• Optimize legacy queries and tune Spark performance for efficiency.
• Collaborate with architects, data scientists, and stakeholders to understand data requirements and deliver robust solutions.
• Ensure data quality, security, and governance across all pipelines.

Skills

Spark

Python

PySpark

Databricks

SQL

ETL/ELT

AWS

GCP

Delta Lake

Job description

# Data EngineerEpam SystemsPosted on October 17, 2026---Experience6 - 11 yrsSalary (CTC)₹30L - ₹45LJob LocationHyderabad, IndiaVacancy1DesignationData EngineerJob TypeNot specified---## Job Description**Senior Data Engineer / Lead Data Engineer (Spark, Python, AWS / GCP / Databricks) - Walk-In Drive(Only Shortlisted will be called for Interview)****Company Name:** EPAM Systems **Location:** Hyderabad **Walk-In Interview Date:** 17-Oct-2026 **Experience Level:** 6 to 15 Years **Notice Period:** 0 to 30 Days (Immediate Joiners Preferred) **Employment Type:** Full Time**About EPAM Systems:**EPAM Systems, Inc. is a leading global provider of digital platform engineering and development services. We are committed to building a better future through our innovative software engineering, design, and consulting solutions. We are currently scaling our Data & Analytics practice and looking for passionate, highly skilled Big Data Professionals to join our growing team in Hyderabad.**Job Description:**We are hiring experienced Senior/Lead Data Engineers with strong expertise in **Spark, Python, and Cloud platforms (AWS or GCP)**, along with hands-on experience in **Databricks**. In this role, you will design, build, and optimize scalable enterprise data pipelines, data lakes, and analytics solutions for our global clients.**Key Responsibilities:*** Design and implement large-scale data ingestion and processing pipelines using **Apache Spark** and **Python**.* Build and maintain high-performance data workflows on **AWS** or **GCP** cloud environments.* Utilize **Databricks** for collaborative data engineering, data science, and pipeline optimization (Delta Lake, Lakehouse architecture).* Optimize legacy queries, tune Spark performance, and ensure efficient resource utilization.* Collaborate with architects, data scientists, and stakeholders to understand data requirements and deliver robust solutions.* Ensure data quality, security, and governance standards are maintained across all pipelines.**Mandatory Skill Sets & Criteria:*** **Primary Tech Stack 1:** Spark, Python, AWS, Databricks* **Primary Tech Stack 2:** Spark, Python, GCP* **Core Skills:** PySpark, SQL, ETL/ELT pipeline development, Cloud Data Warehousing.* **Experience:** **6 to 15 Years** of relevant Big Data Engineering experience.* **Notice Period:** **0 to 30 Days** (Immediate joiners or serving notice period preferred).**Walk-In Drive Details:*** **Date:** 17-Oct-2026* **Note:** **Only shortlisted candidates will be called for the face-to-face interview.** Pre-registration / profile sharing is mandatory to receive the call letter, exact time slot, and venue details.