Engineering Manager with Data Engineering Experience

2 Months ago • 10 Years +

Job Summary

Job Description

We are seeking an experienced Engineering Manager to lead our data engineering team. This role demands a blend of technical leadership and delivery ownership, requiring passion for both high-performing teams and world-class data systems. Responsibilities include leading engineering work on data products across various domains using AWS, leading agile ceremonies, mentoring data and analytics teams, aligning data strategies with company objectives, overseeing product development, providing technical leadership in data warehousing, ETL pipelines, and real-time processing, improving development best practices, collaborating with stakeholders, and ensuring data product reliability and security. The ideal candidate will have a strong background in agile data and analytics development, experience leading teams, proficiency in SQL, Python, and PySpark, and deep knowledge of AWS services.
Must have:
  • 10+ years of experience in agile data and analytics development
  • Proven experience leading high-performing technical teams
  • Proficiency in SQL, Python, and PySpark
  • Experience with batch and real-time data pipelines
  • Deep knowledge of AWS best practices
Good to have:
  • Experience with EMR, S3, Redshift, Glue, Kinesis, Spark, SageMaker, Athena, PowerBI, Snowflake, Oracle, MS SQL, D365
Perks:
  • Flexible working format
  • Competitive salary and compensation package
  • Personalized career growth
  • Professional development tools
  • Education reimbursement
  • Corporate events

Job Details

We are looking for an experienced Engineering Manager to lead our team, responsible for delivering scalable, reliable, and secure data infrastructure and services. This role is a blend of technical leadership and delivery ownership - ideal for someone who is equally passionate about building high-performing teams and world-class data systems. You will ensure the technical feasibility of our data product while empowering the team to deliver high-quality and sustainable solutions. You’ll be accountable for technical execution, managing feasibility risks, guiding architecture, and driving team performance.

 

Responsibilities

  • Delivery: Lead engineering work on a portfolio of innovative data products across payments, subscription, finance domains leveraging modern AWS technology stack. Lead agile ceremonies including planning, refinements, retrospectives, and stand-ups.
  • Team Leadership and Management: guide and mentor data and analytics teams, support team development and allocate team and budget resources effectively.
  • Strategy and Planning: Strong outcome focus to ensure that data and analytics strategies and planning are aligned with the company's objectives and technology roadmap.
  • Product Management: Oversee all phases of data platform and product development from conception to deployment, ensuring they meet quality standards and deadlines.
  • Technical Expertise: Provide technical leadership in areas like data warehousing, data lakes, ETL pipelines, real-time processing, and financial reporting. Improve and enforce development best practices (coding standards, testing, CI/CD, etc.)
  • Stakeholder Engagement: Collaborate with product management and client facing teams to understand analytics and data quality needs and deliver effective solutions.
  • Quality Assurance and Support: Ensure the reliability, scalability, and security of  data products with end to end ownership mindset. Lead technical issue resolution, act as point of escalation for technical blockers and critical bugs and manage technical debt. 

 

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related. 
  • 10+ years hands on experience in agile data and analytics development, with a focus on AWS technologies. 
  • Proven experience in leading and managing high performing technical teams.
  • Previous commercial experience as Data/Big Data Engineer is a must.
  • Proficiency in languages SQL, Python and PySpark.
  • Experience with both batch and real-time data pipelines.
  • Familiarity with observability, reliability, and uptime metrics in data systems.
  • Deep knowledge of AWS best practices and reference architectures.  
  • Familiarity with AWS Services like EMR, S3, Redshift, Glue Data Catalog, Kinesis, Spark, SageMaker, Athena, PowerBI, Snowflake, Oracle, MS SQL, D365. 
  • Excellent project and product management skills.
  • Strong communication and interpersonal skills.

 

We offer*:

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

*not applicable for freelancers

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