Engineering Manager

We are looking for an experienced Data Engineering Manager to lead and scale our data engineering function. The ideal candidate will be responsible for designing, building, and maintaining high-quality data pipelines and platforms that support analytics, reporting, and data-driven decision-making across the organization. This role involves leading a team of data engineers, collaborating with cross-functional stakeholders, and ensuring the reliability, scalability, and performance of our data ecosystem.

Responsibilities :

Lead, mentor, and develop a team of data engineers to deliver high-quality data solutions.

Architect, build, and optimize scalable data pipelines that process structured and unstructured data.

Own the development and maintenance of data architectures, warehouses, lakes, and integration frameworks.

Collaborate closely with analytics, product, engineering, and business teams to understand data needs and translate them into technical solutions.

Implement best practices for data quality, governance, lineage, security, and compliance.

Drive the adoption of modern data engineering tools, frameworks, and cloud technologies.

Monitor and improve pipeline performance, ensuring high availability and reliability.

Manage sprint planning, task prioritization, and project execution.

Oversee data documentation, standards, and operational processes.

Work with leadership to define the data engineering roadmap, capacity planning, and team growth strategies.

Requirements :

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.

8+ years of experience in data engineering, with at least 2-3 years in a leadership or managerial role.

Strong hands-on experience with data pipeline tools and frameworks (e. g., Apache Spark, Kafka, Airflow, dbt).

Expertise in SQL and proficiency in at least one programming language (Python, Java, or Scala).

Experience with cloud platforms such as AWS, Azure, or GCP (data services, storage, compute).

Solid understanding of data modeling, ETL / ELT design, and distributed systems.

Strong knowledge of relational and NoSQL databases.

Experience with CI / CD, automation, version control, and DevOps practices.

Excellent stakeholder management and communication skills.

Preferred Qualifications :

Experience in building data platforms from the ground up.

Prior experience working with real-time streaming architectures.

Familiarity with ML Ops or enabling ML engineering workflows.

Certifications in cloud technologies (AWS, Azure, GCP).

Experience working in Agile environments.

Key Competencies :

Technical leadership.

Strategic thinking.

Problem-solving and analytical abilities.

Team development and mentoring.

Project management.

Stakeholder collaboration.