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Senior Data Engineer - Contract

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Onsite

Senior Data Engineer - Contract

Vidpro Consultancy Services

Senior Data Engineer - Contract

Skills

SQL QueriesBig DataData EngineeringPythonTesting & QAMySQLSnowflakeData AnalysisMachine LearningAIScalaCompliance

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,500,000 – ₹2,500,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

25 August 2026

What they need


  • Job title : Lead / Senior Data Engineer
  • Experience: 8+ years
  • Location: Chennai / Pune / Bangalore / Hyderabad
  • Role Type : Contract (6 Months)
  • Shift : UK Shift ( 2 PM to 11 PM)

Roles and Responsibilities:

Role Overview

  • The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.

Key Responsibilities

  • Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.
  • Define technical strategy, architecture, and best practices for development and data engineering.
  • Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.
  • Construct infrastructure for efficient ETL processes from various sources and storage systems.
  • Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.
  • Lead the implementation of algorithms and prototypes to transform raw data into useful information.
  • Review code for quality, scalability, and performance.
  • Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.
  • Develop analytical tools, programs, and reporting mechanisms.
  • Create data validation methods and data analysis tools.
  • Interpret data trends and patterns to establish operational alerts.
  • Conduct complex data analysis and present results effectively.
  • Prepare data for prescriptive and predictive modeling.
  • Ensure compliance with data governance and security policies.
  • Troubleshoot, debug, and resolve complex technical issues.
  • Drive continuous improvement in software and data development processes, tools, and methodologies.
  • Mentor and guide engineers through code reviews, technical discussions, and training.
  • Ensure timely delivery of projects while maintaining high engineering standards.
  • Continuously explore opportunities to enhance data quality and reliability.
  • Apply strong programming and problem-solving skills to develop scalable solutions.
  • Demonstrate passion for testing strategy, problem-solving, and continuous learning.
  • Willingness to acquire new skills and knowledge.
  • Possess a product/engineering mindset to drive impactful data solutions.
  • Experience working in distributed environments with global teams.
  • Stay current with emerging technologies and industry trends to propose innovative solutions.

Technical Skills and Experience Requirements

  • Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
  • High proficiency in Python, Scala, and Spark for applied large-scale data processing.
  • Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
  • Solid understanding of batch and streaming data processing techniques.
  • Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
  • Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
  • Experience with RDBMS and OLAP databases such as MySQL and Snowflake.
  • Familiarity with Agile methodologies.
  • Obsession for service observability, instrumentation, monitoring, and alerting.
  • Knowledge or experience in architectural best practices for building data lakes.
  • Qualifications -Bachelor’s degree in computer science, Engineering, Information Systems, or related field

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