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182 open roles · AI & Data Engineering

Sr Data Specialist - R01564133

Full-time
Senior
Posted 5 months ago
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Where you can work

Hybrid

2 workplaces

  • Bengaluru, Karnataka, India
  • India
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  • Bangalore, Karnataka, India
  • India (Hybrid/Remote)

Remote

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India (Hybrid/Remote)

Role overview

Extracted from the posting. Read the employer’s full description below.

What they are looking for

  • Design and build scalable data pipelines using Spark / PySpark on Databricks
  • Develop and optimize ETL/ELT workflows for large-scale data processing
  • Work with AWS EMR, S3, and Hadoop ecosystem for distributed data processing
  • Build and maintain data lake and data warehouse solutions
  • Develop and integrate APIs for data ingestion and consumption
Show all 37 items
  • Implement data processing workflows using Airflow / Autosys
  • Optimize data performance using partitioning, caching, and query tuning
  • Handle structured and semi-structured data from multiple sources
  • Ensure data quality, governance, and reliability of pipelines
  • Collaborate with cross-functional teams (Analytics, Product, Engineering)
  • Strong expertise in:
  • Apache Spark / PySpark
  • Databricks (mandatory)
  • SQL (PostgreSQL or similar)
  • Hands-on experience with:
  • AWS EMR, S3
  • Hadoop, Hive ecosystem
  • Programming skills:
  • Python (must-have)
  • Scala (good exposure)
  • Strong knowledge of:
  • UNIX / Shell scripting
  • ETL pipelines and data engineering fundamentals
  • Experience with:
  • Elasticsearch (data storage & retrieval)
  • Workflow orchestration tools (Airflow, Autosys)
  • Exposure to:
  • API development & integration
  • Version control tools ( Git / SVN )
  • Basic knowledge of HTML (for web/data tasks)
  • Minimum 5+ years of Data Engineering experience
  • Strong hands-on experience in Databricks + Big Data stack
  • Proven experience working on large-scale distributed systems
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
  • Work on cloud-native, large-scale data platforms
  • Exposure to cutting-edge Databricks & AWS ecosystems
  • Collaborative and high-performance engineering culture

Employer description

Lead Data Engineer

Primary Skills

  • Athena, Step Functions, Spark - Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Data Modelling Fundamentals, Cloud front

Specialization

  • AWS Data EngineerIng Basic: Senior Data Engineer

Job requirements

Job Description – AWS Senior Data Engineer

Company: Brillio Technologies Role: Senior Data Engineer Experience: 5–10 Years Location: India (Hybrid/Remote) Employment Type: Full-time

Role Overview

We are looking for a Senior Data Engineer with strong Databricks and Big Data expertise to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have hands-on experience with Spark, PySpark, AWS ecosystem, and modern data architectures, along with exposure to APIs and real-time data processing.

Key Responsibilities

  • Design and build scalable data pipelines using Spark / PySpark on Databricks
  • Develop and optimize ETL/ELT workflows for large-scale data processing
  • Work with AWS EMR, S3, and Hadoop ecosystem for distributed data processing
  • Build and maintain data lake and data warehouse solutions
  • Develop and integrate APIs for data ingestion and consumption
  • Implement data processing workflows using Airflow / Autosys
  • Optimize data performance using partitioning, caching, and query tuning
  • Handle structured and semi-structured data from multiple sources
  • Ensure data quality, governance, and reliability of pipelines
  • Collaborate with cross-functional teams (Analytics, Product, Engineering)

Technical Skills (Must-Have)

  • Strong expertise in:
  • Apache Spark / PySpark
  • Databricks (mandatory)
  • SQL (PostgreSQL or similar)
  • Hands-on experience with:
  • AWS EMR, S3
  • Hadoop, Hive ecosystem
  • Programming skills:
  • Python (must-have)
  • Scala (good exposure)
  • Strong knowledge of:
  • UNIX / Shell scripting
  • ETL pipelines and data engineering fundamentals

Additional Skills

  • Experience with:
  • Elasticsearch (data storage & retrieval)
  • Workflow orchestration tools (Airflow, Autosys)
  • Exposure to:
  • API development & integration
  • Version control tools (Git / SVN)
  • Basic knowledge of HTML (for web/data tasks)

Experience Required

  • Minimum 5+ years of Data Engineering experience
  • Strong hands-on experience in Databricks + Big Data stack
  • Proven experience working on large-scale distributed systems

Education

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Why Join Brillio

  • Work on cloud-native, large-scale data platforms
  • Exposure to cutting-edge Databricks & AWS ecosystems
  • Collaborative and high-performance engineering culture
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