Data Engineering Manager

Keylent Inc is seeking a hands-on Data Engineering Manager to lead the data platform supporting fleet and telematics products. The role combines management and mentoring of a small engineering team with direct ownership of production data pipelines, platform reliability, and collaboration with Data Science, product, and engineering teams.

Responsibilities

• Design, build, and maintain production data pipelines and orchestration workflows from ingestion through transformation and serving
• Write and optimize SQL, Python, and PySpark for large-scale data processing
• Develop and operate workflows using Apache Airflow or a comparable orchestration platform
• Build and maintain data solutions using Snowflake and AWS services, including S3 and EMR/Spark
• Develop and improve streaming or event-driven ingestion patterns, including Kafka where appropriate
• Set up data quality checks, pipeline monitoring, alerting, and operational dashboards
• Investigate production issues, lead root-cause analysis, and implement durable corrective actions
• Improve warehouse performance and control platform costs through query optimization, resource sizing, and scheduling strategies
• Contribute directly to code reviews, technical design, testing, and deployment
• Manage and mentor the Senior Data Engineer and Data Engineer, providing technical guidance, feedback, and development support
• Set clear priorities and delivery expectations, balancing project work with platform health and operational responsibilities
• Support team members in design reviews, troubleshooting, and delivery planning while encouraging ownership and sound engineering practices
• Coordinate work across data engineering, Data Science, product, and software engineering teams
• Communicate progress, risks, dependencies, and technical tradeoffs to stakeholders
• Establish practical standards for data architecture, pipeline development, testing, documentation, and production readiness
• Partner with Data Science to support feature engineering and data pipelines for machine learning and analytics workloads
• Collaborate with product and engineering stakeholders to translate business needs into reliable and scalable data solutions
• Document platform architecture and key pipeline designs to support maintenance and onboarding
• Identify opportunities to simplify, modernize, or automate the data platform as product needs and data volumes grow

Skills

• 5+ years of experience in data engineering, including hands-on ownership of production data pipelines
• Experience leading, mentoring, or managing data engineers
• Strong SQL skills, including query analysis and optimization
• Proficiency in Python and PySpark for distributed data processing
• Hands-on experience with a cloud data warehouse such as Snowflake
• Experience with workflow orchestration, such as Apache Airflow
• Experience with AWS data infrastructure, including cloud storage and distributed processing such as S3 and EMR/Spark
• Experience building and operating data pipelines in production, including monitoring, data quality, and incident response
• Understanding of data warehouse design, data modeling, and ETL/ELT patterns
• Strong communication skills and the ability to explain technical decisions to technical and non-technical stakeholders
• Experience with Kafka or other streaming and change-data-capture (CDC) technologies
• Experience with relational databases such as PostgreSQL
• Familiarity with data quality and observability frameworks
• Exposure to ML and analytics pipeline support, including feature engineering or model-serving data preparation
• Familiarity with monitoring and logging tools such as Dynatrace, Prometheus, Grafana, or the ELK stack
• Experience with CI/CD, infrastructure automation, and DevOps practices
• Familiarity with Docker and container orchestration platforms such as Kubernetes or OpenShift
• Experience with collaboration and delivery tools such as Jira, Bamboo, Bitbucket, or Confluence
• Relevant certifications, such as SnowPro or AWS data certifications

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