Role Overview
We are looking for a sharp, hands-on Engineering Manager to lead, mentor, and scale a hybrid team of Data Engineers and Data Analysts. In this role, you won't just be managing spreadsheets and standups; you will be the strategic bridge between robust data infrastructure and actionable business intelligence.
The ideal candidate has walked the walk as a heavy-hitting Data Engineer, transitioned into a high-impact technical leadership role, and fundamentally understands how data analysts consume data to drive business decisions. If you love building scalable pipelines but get equally excited about clean data models that empower analysts to deliver killer insights, we want to talk to you.
What You’ll Do
● People Leadership: Manage, mentor, and grow a talented team of Data Engineers and Data Analysts. Conduct regular 1-on-1s, guide career development, and foster a collaborative, high-performance team culture.
● Technical Strategy & Architecture: Partner with engineering and product leaders to design and execute our data roadmap. Ensure our data platform is scalable, reliable, and optimized for both production systems and analytical queries.
● Bridge the Gap: Act as the connective tissue between engineering and analytics. Ensure data pipelines are built with the end-user (the analyst and business stakeholder) in mind, championing data quality, clear documentation, and intuitive data modeling.
● Delivery & Execution: Own the delivery of data infrastructure projects and analytics initiatives. Balance technical debt with the delivery of high-value business features using agile methodologies.
● Hands-on Guidance: While this is a management role, you aren't afraid to dive into a code review, unblock a tricky SQL query, or help architect a complex data pipeline when the team needs it.
What You Bring
● Technical Leadership: 1–3 years of experience serving as a Technical Lead, Scrum Master, or Staff Engineer, with a proven track record of guiding technical decisions and mentoring peers.
● Deep Individual Contributor (IC) Roots: Minimum of 5–7 years of hands-on experience as an IC Data Engineer building scalable production data pipelines, ETL/ELT workflows, and managing data warehouses (e.g., Snowflake, BigQuery, Redshift).
● Streaming & Ingestion Expertise: Direct, hands-on experience utilizing Apache Kafka and Apache Flink for high-throughput, real-time data ingestion and stream processing.
● Analyst-Centric Mindset: A strong history of working very closely with Data Analysts. You understand their pain points, speak their language, and have deep experience with data modeling frameworks (like dbt) and BI tools (like Tableau, Looker, or PowerBI).
● Core Technical Skills: Proficient in Python, advanced SQL, data orchestration tools (like Airflow or Prefect), and modern data architecture principles.
● Communication Skills: Exceptional communication skills with the ability to translate complex technical concepts into clear business outcomes for non-technical stakeholders.
Bonus Points If You Have
● Experience working within media streaming companies and developing data solutions for consumer-driven applications.
● Experience managing hybrid teams consisting of both engineering and analytics skill sets.
● Familiarity with data governance, security compliance, and data privacy regulations.
● Experience scaling data teams in a fast-paced, high-growth environment.
