Manager, Data Analytics and Engineering

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We are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates.Full-TimeManager

Salary215,000 - 235,000 USD per year

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Job Details

Experience: 8+ years of experience in Data Engineering or related roles; 3+ years leading engineers (hiring, coaching, delivery accountability).
Required Skills: PythonSQLJavaKafkaAirflowData engineeringData modelingDistributed Systems

Graduate degree in Computer Science, Mathematics, or a related quantitative field.
8+ years of experience in Data Engineering or related roles.
3+ years leading engineers, including hiring, coaching, and delivery accountability.
Strong distributed systems fundamentals, including scaling, reliability, and data correctness.
Hands-on ability in Python and/or Java, with the ability to dive into code and unblock delivery.
Experience with a cloud data ecosystem: GCP preferred, or AWS or Azure.
Proficiency with SQL and at least one programming language: Python, Java, or Scala.
Experience with orchestration tools such as Airflow or Argo.
Understanding of data modeling, ETL/ELT patterns, and data reliability.
Experience with streaming technologies such as Kafka, Flink, or Spark Streaming.
Experience with data warehouses or lakehouses such as BigQuery, Snowflake, Redshift, or Iceberg.
Familiarity with analytics engineering tools such as dbt and semantic layers; exposure to data governance, observability, and data quality tooling.

Lead, mentor, and develop a team of Data Engineers through regular 1:1s, coaching, and performance feedback.
Own hiring, onboarding, career development, and performance management for the team.
Set technical direction and own the design, development, and operation of batch and streaming data pipelines and analytical models.
Ensure data systems are reliable, scalable, performant, and cost-efficient.
Drive best practices in data modeling, data quality, observability, and operational excellence.
Review and guide technical designs, architecture decisions, and code quality.
Translate business and analytics requirements into scalable technical solutions and deliver trusted datasets and metrics with partner teams.
Own sprint planning, prioritization, and delivery commitments; communicate progress, risks, and tradeoffs to stakeholders and leadership.
Establish data engineering standards, patterns, and documentation; support data governance, data contracts, and schema management.
Ensure compliance with security, privacy, and data retention requirements.

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