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# Manager, Data Analytics and Engineering

- **Company:** Prizepicks Llc
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $215,000.0 - $235,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, BigQuery, Cloud Database, Software Quality, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Retention, Data Systems, Data Warehousing, Distributed Systems, Python (Programming Language), Scrum Methodology, Software Tools, SQL Databases, Workflow Management Systems, Data Ingestion, Snowflake, Data Layers, Information Technology, Apache Flink, Data Analytics, Apache Kafka, Spark Streaming, Video Streaming, Amazon Redshift, Programming Languages
- **Published:** October 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=5f7d7d60c6d8e1c7

## About the Role

* A 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 (hiring, coaching, delivery accountability).
 * Strong distributed systems fundamentals (scaling, reliability, data correctness).
 * Hands-on ability in Python and/or Java (can dive into code and unblock delivery).
 * Experience with cloud data ecosystems (GCP - Preferred, AWS, or Azure)
 * Proficiency with SQL and at least one programming language (Python, Java, or Scala)
 * Experience with orchestration tools (Airflow, Argo, etc.)
 * Solid understanding of data modeling, ETL/ELT patterns, and data reliability
 * Experience with streaming technologies (Kafka, Flink, Spark Streaming)
 * Experience with modern data warehouses / lakehouses (BigQuery, Snowflake, Redshift, Iceberg)
 * Familiarity with analytics engineering tools (dbt, semantic layers)
 * Exposure to data governance, observability, and data quality tooling
 * Self-starter + ownership: drives ambiguous problems to durable solutions.
 * Builds and grows teams: mentors, raises the bar, and develops talent.
 * Quality-first: designs for operability, correctness, and reliability from day one., You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

## Description

We are looking for a Data and Analytics Engineering Manager to lead a team responsible for building and operating scalable, reliable, and high-quality data engineering pipelines producing analytical data products. This role blends people leadership, technical stewardship, and cross-functional collaboration to ensure data is trusted, accessible, and delivered in support of analytics, AI, and business decision-making., You will manage a team of data engineers, set technical direction, and partner closely with Product, Analytics, Infrastructure, and Business stakeholders to deliver high-impact data solutions., * 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
 * Foster a culture of accountability, ownership, collaboration, and continuous improvement
 * Balance delivery expectations with sustainable team practices

Technical & Delivery Ownership

 * Own the design, development, and operation of data ingestion, transformation, storage pipelines (batch and streaming), and analytical model(s)
 * Ensure reliability, scalability, performance, and cost efficiency of data systems
 * Drive best practices in data modeling, data quality, observability, and operational excellence
 * Review and guide technical designs, architecture decisions, and code quality
 * Partner with platform and infrastructure teams on tooling, security, and scalability

Execution & Stakeholder Collaboration

 * Translate business and analytics requirements into scalable technical solutions
 * Partner with Product, Analytics Engineering, Data Science, and Business teams to deliver trusted datasets and metrics
 * Own sprint planning, prioritization, and delivery commitments
 * Communicate progress, risks, and tradeoffs clearly to stakeholders and leadership

Governance & Standards

 * Establish and enforce data engineering standards, patterns, and documentation
 * Support data governance, data contracts, and schema management
 * Ensure compliance with security, privacy, and data retention requirements