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Data Engineering Manager

K&C·Salary not specified

Primary stack

NoSQLAthenaDebeziumKafkaAWS GluePythonAirflowSupersetAmazon RedshiftJava

Nice to have's

dbtTrino / PrestoClickHouseApache DruidGitHub ActionsTerraform / CloudFormationAWS certificationsGCC or MENA region experience

Job description

About the Position

We are seeking a Data Engineering Manager to lead a team of data engineers in building streaming and batch data platforms on AWS. You will be accountable for real-time pipelines, data lake and lakehouse management, and the internal frameworks that keep data reliable, discoverable, and fast to consume. The role combines hands-on technical depth with people leadership, delivery ownership, and stakeholder engagement.

Key Responsibilities

  • Define and own the Data Engineering Roadmap, aligning platform priorities with business and analytics goals
  • Design, build, and operate real-time data pipelines using Apache Kafka / Amazon MSK and Debezium-based change data capture (CDC)
  • Manage and evolve the data lake and lakehouse on S3, using Apache Iceberg, Parquet, and Avro, with Glue and Athena for cataloguing and query
  • Architect and maintain analytical serving layers using Apache Pinot, Redshift, and NoSQL / RocksDB-based stores
  • Develop custom frameworks in Java and Python for ingestion, transformation, data quality, and pipeline orchestration
  • Orchestrate batch and streaming workflows with Apache Airflow
  • Design data models for analytical, operational, and real-time use cases
  • Evaluate, implement, and operate open-source data platforms, balancing capability, cost, and maintainability
  • Enable self-service analytics and visualization through Apache Superset
  • Deploy and run data services on ECS / EKS using Docker and infrastructure as code (Terraform / CDK)
  • Establish standards for data quality, observability, lineage, security, and cost optimization
  • Mentor, coach, and grow data engineers, run code and design reviews, and manage team delivery
  • Partner with data scientists, analysts, product owners, and client stakeholders to translate requirements into technical plans
  • Report on delivery progress, risks, and platform health to senior stakeholders

Required Skills and Qualifications

  • 10-15 years of experience in data engineering, including at least 3 years leading or managing engineering teams
  • Strong hands-on experience with Apache Kafka / Amazon MSK and Debezium CDC
  • Experience with Apache Pinot or comparable real-time OLAP systems
  • Proficiency with Amazon Redshift, AWS Glue, Athena, and S3
  • Experience with RocksDB / NoSQL data stores
  • Strong programming skills in Java and Python
  • Hands-on experience with Apache Airflow and Apache Superset
  • Working knowledge of Apache Iceberg and data lake architecture
  • Solid understanding of streaming and batch processing, CDC patterns, and columnar/serialization formats (Parquet, Avro)
  • Experience with ECS / EKS, Docker, and Terraform / CDK
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Nice to Have

  • dbt for transformation and analytics engineering
  • Trino / Presto, ClickHouse, or Apache Druid
  • GitHub Actions and CI/CD pipeline design
  • Terraform / CloudFormation at scale
  • AWS certifications (Data Analytics, Solutions Architect, or DevOps)
  • Experience delivering projects in the GCC or MENA region

Soft Skills

  • Confident people leadership: hiring, mentoring, performance management, and team building
  • Clear communication with technical and non-technical stakeholders
  • Ownership mindset, structured problem solving, and sound architectural judgment
  • Ability to lead effectively in a remote or distributed team

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Київ, Баку (Азербайджан), Краків (Польща), Мюнхен (Німеччина), Прага (Чехія), Софія (Болгарія)

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