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Posted 7 months ago

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Staff Data Engineer

PuneOn-siteFull-time

AI Summary

Staff Data Engineer leading data modeling, ETL/ELT pipelines, and architectural direction to deliver trusted, scalable data assets and a single source of truth for analytics, AI/ML, and stakeholders.

About this role

Role Overview

As a Staff Data Engineer, you’ll be a technical leader and systems thinker within Pattern’s Data Engineering team—designing and scaling our canonical data model to deliver trusted, high-quality data. You’ll transform complex, raw data with a set of efficient pipelines into tables that are easy to understand and efficient to power analytics, forecasting, and AI/ML. You’ll lead through influence, shaping technical direction, mentoring engineers, and building the “single source of truth” that drives Pattern’s global growth.

Roles and Responsibilities

  • Design and evolve canonical and medallion-layer data models (bronze/silver/gold) that enable scalable, governed data across the organization.
  • Build and optimize ETL/ELT pipelines using Apache Airflow, Spark, Trino and cloud-native tools.
  • Develop high-performance data marts and semantic layers that serve analytics and data science needs.
  • Architect streaming and analytical systems using Kafka and ClickHouse for real-time and batch insights.
  • Define and enforce standards for data modeling, documentation, quality, and lineage across all domains.
  • Partner with Analytics, AI/ML, and Infrastructure teams to translate business logic into reusable, trusted data assets.
  • Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability.
  • Champion a culture of data clarity, consistency, and craftsmanship, aligning systems to business goals.

    • Required Qualification

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
  • 10+ years of experience in Data Engineering, including 2+ years in a senior or staff-level technical role.
  • Expertise in SQL, data modeling, and data mart design.
  • Deep hands-on experience with Apache Airflow, dbt, Spark, Kafka, and ClickHouse.
  • Proven experience designing medallion data architectures and scalable data lakehouse solutions.
  • Proficiency in Python or Scala, and familiarity with AWS, GCP, or Azure data ecosystems.
  • Strong understanding of data governance, lineage, and quality frameworks.
  • Demonstrated ability to mentor engineers and influence architectural strategy across teams.

    • Preferred Qualification

  • Experience with real-time or streaming data (Kafka, Kinesis, or Pub/Sub).
  • Knowledge of data observability and catalog tools (DataHub, Amundsen, Monte Carlo, Great Expectations, or Soda).
  • Experience in eCommerce, retail analytics, or digital marketplaces.
  • Exposure to governed data contracts and semantic layer frameworks.
  • Proven track record of leading data architecture initiatives or cross-functional platform modernization.
  • Contributions to open-source data tools or engagement in data community initiatives

    • Skills

    Apache AirflowAWSAzureBI ToolsClickHouseData Catalog ToolsData GovernanceData LineageData Mart DesignData ModelingData QualityDbtELTETLGCPKafkaLakehouseMedallion Data ArchitecturePythonReal-time Data PipelinesScalaSemantic LayerSparkSQL

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