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9 Weeks ago

Senior Big Data Engineer - Python, Spark, SQL

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Information Technology
Other
McKinsey & Company

Overview

Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

Your Impact

You will be a core member of Periscope’s product engineering team with responsibilities that range from developing and deploying our core enterprise products to ensuring that McKinsey’s craft stays on the leading edge of technology.
In this role you will develop and maintain Python/PySpark libraries for data ingestion, incorporating Slowly Changing Dimensions (SCD) logic for efficient ETL workflows. You will create and enhance Python/PySpark libraries for data quality validation, ensuring accuracy, consistency, and completeness in large-scale datasets. You will design and optimize scalable data pipelines leveraging Spark, Databricks, and cloud data services (Azure/AWS).
You will be leading and executing data engineering projects from inception to completion, ensuring timely delivery and high quality while you continuously monitor, troubleshoot, and improve data pipelines and workflows to ensure optimal performance and cost-effectiveness.
You will collaborate with cross-functional teams to stay ahead of emerging trends in Gen AI, big data, and cloud-based automation.

Your Growth

You will be based in our Bangalore or Gurugram office as a member of Periscope’s technology team.
Periscope is the asset-based arm of McKinsey’s Marketing & Sales practice and is at the leading edge of the new ways we serve clients. This integrated model of serving clients, i.e. combining our generalist consulting approaches with the solutions, is a proof of the firm’s commitment to continued innovation in the spirit of bringing the best of the firm to our clients.
Periscope® By McKinsey enables better commercial decisions by uncovering actionable insights. The Periscope platform combines world leading intellectual property, prescriptive analytics, and cloud-based tools to provide more than 25 solutions focused on insights and marketing, with expert support and training. It is a unique combination that drives revenue growth both now and in the future. Customer experience, performance, pricing, category, and sales optimization are powered by the Periscope platform. Periscope has a presence in 26 locations across 16 countries with a team of 600+ business and IT professionals and a network of 300+ experts. To learn more about how Periscope’s solutions and experts are helping businesses continually drive better performance, visit https://www.mckinsey.com/capabilities/growth-marketing-and-sales/solutions/periscope/overview

Your qualifications and skills

  • 6+ years of experience in big data engineering and cloud technologies (Azure/AWS).
  • Proficiency in PySpark, Spark SQL, and Python for data processing and automation.
  • Strong background in building and maintaining Python/PySpark libraries for data ingestion (SCD logic) and data quality validation.
  • Proficiency in distributed computing, Databricks workflows, and Spark optimizations.
  • Experience in API development, SOA architectures and REST services.
  • Experience with streaming data processing (Kafka, Kinesis, Spark Streaming).
  • Implement Gen AI engineering and automation using Databricks capabilities like DB Apps, Genie to enhance data workflows and decision-making.
  • Exposure to LLM fine-tuning, vector databases, and AI-driven analytics.
  • Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and DevOps best practices.
  • Experience with cloud data services such as Azure Data Factory, ADLS, S3 etc.
  • Strong understanding of data governance, security, and compliance in cloud environments.
  • Technical credibility through full-stack or backend software engineering experience.
  • Excellent problem-solving skills with a focus on cost and performance optimization.
  • Actively coached, mentored and grown team members in their careers
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