Data Engineer

Remote

Zelus Analytics

View company page

We are not actively hiring. This job post is to submit your resume off-cycle.

Thank you for your interest in Zelus Analytics. We are always inspired to hear of individuals who are as passionate about sports analytics as we are! Even when we are not in a specific hiring cycle, we welcome folks who are pursuing a data engineering career in sports analytics to submit their resume for future consideration!

We seek data engineers with a passion for sports to develop cloud-based data pipelines and automated data processing for our world-class sports intelligence platforms in baseball, basketball, cricket, football (American), hockey, soccer, and tennis. Through your work, you can support the professional teams in our exclusive partner network in their efforts to compete and win championships. We often have both entry-level and senior positions available, allowing us to consider qualified candidates with a wide range of experience levels.

Zelus Analytics unites a fast-growing startup environment with a research-focused culture that embraces our core values of integrity, innovation, and inclusion. We pride ourselves on providing meaningful mentorship that offers our team the opportunity to develop and expand their skill sets while also engaging with the broader analytics community. In doing so, we hope to create a new path for a more diverse group of highly talented people to push the cutting edge of sports analytics.

We believe that a diverse team is vital to building the world’s best sports intelligence platform. Thus, we strongly encourage you to apply if you identify with any marginalized community across race, ethnicity, gender, sexual orientation, veteran status, or disability. At Zelus, we are committed to creating an inclusive environment where all of our employees are enabled and empowered to succeed and thrive.

As a Zelus Data Engineer, you will be expected to:

  • Design, develop, document, and maintain the schemas and ETL pipelines for our internal sports databases and data warehouses
  • Implement and test collection, mapping, and storage procedures for secure access to team, league, and third-party data sources
  • Develop algorithms for quality assurance and imputation to prepare data for exploratory analysis and quantitative modeling
  • Profile and optimize automated data processing tasks
  • Coordinate with data providers around planned changes to raw data feeds
  • Deploy and maintain system and database monitoring tools
  • Collaborate and communicate effectively in a distributed work environment
  • Fulfill other related duties and responsibilities, including rotating platform support

In addition to the above, a Senior Data Engineer will be expected to:

  • Break down complex data engineering projects into actionable work plans including proposed task assignments for one to four engineers
  • Identify and recommend new ETL tools and novel data sources to push the cutting edge of our sports intelligence platforms
  • Provide guidance and technical mentorship for junior engineers 
  • Assist with recruiting and outreach for the engineering team, including building a diverse network of future candidates

A qualified entry-level candidate will be able to demonstrate several of the following and will be excited to learn the rest through the mentorship provided at Zelus:

  • Academic and/or industry experience in back-end software design and development
  • Experience with ETL architecture and development in a cloud-based environment
  • Fluency in SQL development and an understanding of database and data warehousing technologies
  • Proficiency with Python (preferred), Scala, and/or other data-oriented programming languages
  • Experience with automated data quality validation across large data sets
  • Familiarity working with Linux servers in a virtualized/distributed environment
  • Strong software-engineering and problem-solving skills

A qualified senior candidate will be able to demonstrate all of the above at a higher level of competency plus the following:

  • Expertise developing complex databases and data warehouses for large-scale, cloud-based analytics systems
  • Experience with task orchestration and workflow automation tools (Airflow preferred)
  • Experience building and overseeing team-wide data quality initiatives
  • Experience adapting, retraining, and retooling in a rapidly changing technology environment
  • Desire and ability to successfully mentor junior engineers

Zelus has a fully distributed workforce, spanning thirteen states and seven countries as of the end of 2022. In addition to competitive salaries, our compensation packages include equity and benefits, such as an annual incentive bonus plan and flexible PTO, that allow us to attract and retain a world-class team.

As an equal opportunity employer, Zelus does not discriminate on the basis of race, ethnicity, color, religion, creed, gender, gender expression or identification, sexual orientation, marital status, age, national origin, disability, genetic information, military status, or any other characteristic protected by law. It is our policy to provide reasonable accommodations for applicants and employees with disabilities. Please let us know if reasonable accommodation is needed to participate in the job application or interview process.

Zelus is an at-will employer; employment at Zelus is for an indefinite period of time and is subject to termination by the employer or the employee at any time, with or without cause or notice.

Pay: $75,000.00 - $150,000.00 per year

Apply now Apply later
  • Share this job via
  • or

Tags: Airflow Architecture Data pipelines Data quality Data Warehousing Engineering ETL Linux Pipelines Python Research Scala SQL

Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Salary bonus Startup environment

Region: Remote/Anywhere
Job stats:  48  4  0
Category: Engineering Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.