Sr. Data Engineer (Databricks)

Blumetra Solutions; Hyderabad; Hybrid; INR 1,200,000 - 1,500,000; Full time

Job summary

Blumetra Solutions in Hyderabad is seeking a highly skilled Senior Data Engineer proficient in PySpark, Databricks, and SQL. This role involves designing and developing scalable data pipelines, optimizing performance, and implementing CI/CD practices.

The ideal candidate will have 6-8 years of experience in data engineering, hands-on expertise in building enterprise-scale data solutions, and a hybrid work model that offers flexibility. Join us to lead innovation in our data architecture.

Qualifications

• 6 - 8 years of experience in data engineering.
• Strong hands-on experience with Python/PySpark.
• Expertise in Databricks and advanced SQL capability.

Responsibilities

• Design and develop scalable data pipelines using PySpark and Databricks.
• Optimize workloads for performance and cost efficiency.
• Provide technical leadership and mentor engineering teams.

Skills

Databricks

Python/PySpark

SQL

Tools

AWS

Azure

Snowflake

DBT

Kafka/Event Hub/Kinesis

Airflow

Terraform

Unity Catalog

Delta Live Tables

Job description

Experience

6 - 8 years

Mandatory Skills

Databricks, Python/Pyspark, SQL

Job Summary

We are seeking a highly skilled Senior Data Engineer with strong expertise in PySpark, Databricks, and SQL. The ideal candidate should have hands‑on experience building enterprise‑scale batch and real‑time data pipelines, optimizing high‑volume workloads, and designing modern data architectures.

Work Location

Hyderabad (Hybrid Model)

Prestige Skytech, Financial District

Key Responsibilities

• Design and develop scalable batch and streaming data pipelines using PySpark and Databricks
• Build and optimize enterprise data models and transformation pipelines using Snowflake and DBT
• Develop advanced SQL scripts, stored procedures, and performance-optimized queries
• Design and implement real-time streaming architectures
• Build integrations using APIs, event-driven architectures, and cloud-native services
• Optimize workloads for performance, scalability, and cost efficiency
• Design enterprise data platforms using Lakehouse, Data Mesh, Data Vault, and Fabric principles
• Work with cross‑functional teams to build scalable analytics and data engineering solutions
• Implement CI/CD and DevOps practices for data engineering pipelines
• Provide technical leadership and mentor engineering teams

Required Skills

• Strong hands‑on experience with Python / PySpark
• Expertise in Databricks
• Advanced SQL expertise
• Strong experience with Stored Procedures and complex SQL optimization
• Hands‑on experience with streaming frameworks and real‑time processing
• Experience with REST APIs and enterprise integrations
• Strong understanding of distributed data processing
• Working knowledge of AWS and/or Azure
• Excellent analytical and debugging skills

Strong Knowledge Of

• Data Warehousing
• Data Vault Modeling
• Data Mesh
• Data Lake & Lakehouse Architecture
• Enterprise Data Architecture Patterns

Good to Have

• Kafka/Event Hub/Kinesis
• Airflow
• Terraform
• Unity Catalog
• Delta Live Tables
• CI/CD pipelines