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remoteroles

Data Engineer

SumerSports LLC Open · verified Oct 24, 2026
Remote United States Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at SumerSports LLC. Remote, United States · full-time · no salary stated · we estimate $112,500–$160,000 across the United States.

Estimated pay

SumerSports LLC has not published a salary for this role. The figure below is our estimate, not theirs.

$112,500 – $160,000
What the middle half of mid-level data engineering roles in the United States paid, among postings that did state a salary.
Worked out from 386 postings that stated pay, median $134,547. Last updated Oct 24, 2026.
RoleData Engineering
SeniorityMid-level
LocationUnited States
WorkplaceRemote
EmploymentFull-time
PostedSep 10, 2026 · 6w ago
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Build data pipelines that ingest, clean and reshape information for batch and streaming use
  • Create retrieval workflows over statistics, scouting notes and video metadata for AI applications
  • Prepare datasets for ML teams and make them usable by autonomous agents with query checks and safeguards
  • Organize and monitor scheduled jobs, tracing dependencies and setting up recovery when runs fail
  • Maintain dependable data assets, enforce validation and schemas, and improve platform performance and cost

What you bring

  • You have three to eight years building data systems or ETL workflows in production
  • You work proficiently in Python and SQL, with strong knowledge of Databricks, Spark or a comparable framework
  • You understand data modeling, warehousing, distributed processing and current lakehouse designs
  • You have used orchestration software such as Airflow, Dagster or another listed tool

Who this fits

This mid-level role suits a data engineer who can work across ingestion, transformation and orchestration while partnering with ML, product and analytics teams. The position is remote within the United States.

From the employer

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.


Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more.


What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.

Position Summary


Our data engineering team is the foundation of this system, ensuring data is accurate, fast, and always available for our models and AI applications.


As a Data Engineer, you’ll design, build, and maintain the data pipelines that power our deep learning, video and LLM systems. You’ll work across ingestion, transformation, and orchestration layers — from real-time feeds to analytics-ready datasets. Your mission is to make data reliable, discoverable, and scalable for use by model training, analytics, and AI-driven products across multiple sports. You’ll collaborate closely with our MLOps, and Sports Data teams to ensure seamless integration between data and AI.


Responsibilities

  • Build and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Kubernetes.
  • Develop efficient ETL/ELT workflows in Python and SQL to support both batch and streaming workloads.
  • Partner with ML/AI teams to make datasets and tools discoverable and safe for autonomous agents, including evaluation and guardrails for AI-generated queries.
  • Develop retrieval pipelines (RAG, vector search) over structured stats and unstructured sources (scouting notes, video metadata) to power AI applications.
  • Model and maintain structured data assets (Delta, Parquet, Iceberg) for reliability, versioning, and lineage tracking.
  • Implement orchestration and monitoring: schedule jobs, track dependencies, and automate recovery from failures.
  • Ensure data quality and compliance through validation frameworks, schema enforcement, and audit logging.
  • Contribute to data platform evolution: evaluate tools, standardize best practices, and improve developer experience.
  • Support performance and cost optimization across compute, storage, and orchestration systems.


Qualifications

  • 3–8 years of experience as a Data Engineer or ETL Developer in a production environment.
  • Proficiency in Python and SQL; strong familiarity with Databricks, Spark, or equivalent big-data frameworks.
  • Experience with workflow orchestration tools such as Airflow, Dagster, Luigi or Prefect.
  • Deep understanding of data modeling, data warehousing, and distributed data processing.
  • Knowledge of modern data lakehouse architectures.
  • Familiarity with CI/CD, GitHub Actions, Infrastructure as Code, and data pipeline testing frameworks.
  • Comfort working in a cross-functional environment with ML, product, and analytics teams.
  • Exposure to LLM-powered data tools: text-to-SQL, RAG, agent/tool interfaces (e.g. MCP), or natural-language analytics.
  • Previous work with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Docker, Kubernetes).


Preferred

  • Previous experience with sports, telemetry, or sensor data pipelines.
  • Familiarity with streaming frameworks and event driven data processing (Kafka, Spark Structured Streaming, Flink).
  • General knowledge of American football, the NFL, and college football.
  • Background in data governance, lineage, and observability tools (Monte Carlo, Great Expectations, Unity Catalog, OpenLineage).
  • Experience designing semantic layers or metric definitions consumed by AI and BI tools.
  • Exposure to best practices in machine-learning model management and MLOps.


Benefits

  • Competitive Salary and Bonus Plan
  • Comprehensive health insurance plan
  • Retirement savings plan (401k) with company match
  • Remote working environment
  • A flexible, unlimited time off policy
  • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl


SumerSports is committed to fair and equitable compensation practices.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.


The total compensation package for this position may also include annual performance bonus, benefits and/or other applicable incentive compensation plans.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data EngineeringRemote

Find me work

By the team behind remoteroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.