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Data Engineer

Roles & Responsibilities

  • 12+ years of data engineering experience with proven leadership of teams (8–20 engineers).
  • Hands-on experience with modern data stack: SQL/NoSQL databases, ETL/ELT tools, and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
  • Proficiency in programming languages such as Python, Java, or Scala; experience with Apache Spark, Hadoop, or Kafka.
  • Strong cloud platform expertise (AWS, Azure, or Google Cloud) and deep understanding of data modeling, architecture, lifecycle management, governance, security, and compliance; familiarity with CI/CD and infrastructure-as-code.

Requirements:

  • Lead and manage a team of data engineers, fostering a culture of innovation, ownership, and continuous improvement; define and execute the data engineering roadmap aligned with organizational goals and product strategy.
  • Architect, design, and oversee scalable, reliable, and high-performance data pipelines and data platforms; collaborate with Product, Analytics, Data Science, and DevOps to deliver end-to-end data solutions.
  • Establish best practices for data governance, data quality, security, and compliance; drive adoption of modern data technologies; ensure systems are future-ready and cost-efficient.
  • Mentor team members, monitor system reliability and performance, manage stakeholder expectations, and ensure timely delivery of projects.

Job description

This role is for one of the Weekday's clients

Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)

Min Experience: 12 years

Location: Remote (India)

JobType: full-time

We are seeking an accomplished Engineering Manager – Data Engineering to lead the design, development, and scaling of robust data platforms and pipelines. This role is ideal for a seasoned professional who combines deep technical expertise in data engineering with strong leadership capabilities. You will be responsible for driving data strategy, mentoring high-performing teams, and delivering scalable data solutions that power business intelligence, analytics, and advanced applications such as AI/ML.

Requirements

Key Responsibilities:

  • Lead and manage a team of data engineers, fostering a culture of innovation, ownership, and continuous improvement.
  • Define and execute the data engineering roadmap aligned with organizational goals and product strategy.
  • Architect, design, and oversee the implementation of scalable, reliable, and high-performance data pipelines and data platforms.
  • Collaborate with cross-functional teams including Product, Analytics, Data Science, and DevOps to deliver end-to-end data solutions.
  • Establish best practices for data governance, data quality, security, and compliance.
  • Drive the adoption of modern data technologies and frameworks, ensuring systems are future-ready and cost-efficient.
  • Review system architecture and code to ensure scalability, maintainability, and performance optimization.
  • Manage stakeholder expectations, prioritize initiatives, and ensure timely delivery of projects.
  • Mentor team members, support career growth, and build leadership within the team.
  • Monitor and improve system reliability, uptime, and performance through proactive measures and observability tools.

Required Skills & Expertise:

  • Strong experience in data engineering, including building large-scale data pipelines and distributed systems.
  • Hands-on expertise with modern data stack technologies such as SQL/NoSQL databases, ETL/ELT tools, and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Experience with big data technologies like Apache Spark, Hadoop, or Kafka.
  • Deep understanding of cloud platforms such as AWS, Azure, or Google Cloud.
  • Strong knowledge of data modeling, data architecture, and data lifecycle management.
  • Experience implementing data governance, security, and compliance frameworks.
  • Familiarity with CI/CD pipelines, DevOps practices, and infrastructure-as-code tools.
  • Proven track record of leading and scaling high-performing engineering teams.

Leadership & Management Expectations:

  • Demonstrated ability to lead teams of 8–20 engineers, including senior and lead engineers.
  • Strong decision-making skills with the ability to balance technical depth and business priorities.
  • Excellent communication and stakeholder management skills.
  • Experience in agile development methodologies and delivering large-scale projects.
  • Ability to influence technical direction and drive organizational change.

Preferred Qualifications:

  • Experience in building data platforms for AI/ML use cases.
  • Exposure to real-time data processing and streaming architectures.
  • Prior experience in enterprise-scale or high-growth environments.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

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