Technical Lead - Analytics Engineer

Rush Street
Malta, Kärnten, Austria
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Malta, Kärnten, Austria

Tech stack

Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Azure
Google BigQuery
Cloud Computing
Data Validation
Information Engineering
Data Mart
Data Warehousing
Dimensional Modeling
Python
Software Architecture
SQL Databases
Snowflake
Containerization
Core Data
Kubernetes
Information Technology
REST
Docker
Redshift

Job description

The Analytics Engineering Technical Lead will define and own the modeling architecture, standards, and technical direction within RSI's cloud-native Data Platform. This role is accountable for ensuring that analytics-ready data is reliable, scalable, and aligned to long-term business needs across growth, operations, and risk.

You will lead the design and governance of core data models in Snowflake and dbt, establishing best practices that enable high-quality, self-service analytics without sacrificing trust or performance. As a hands-on technical leader, you will set standards for modeling, testing, documentation, and deployment while mentoring other Analytics Engineers and raising the overall technical bar of the team.

This role partners closely with Data Engineering, Analytics, and business stakeholders to translate evolving requirements into durable data products. You will help balance speed and governance, prioritize platform investments, and ensure our data foundation scales with the business.

Our modern data stack includes Snowflake, AWS, Python, Airflow, and dbt.

What You'll Do:

  • Lead the design, development, and lifecycle management of curated datasets, dbt models, and analytics data marts aligned to business domains and metrics.
  • Establish and evolve standards and best practices for dbt modeling, testing, documentation, and code organization to support long-term scalability.
  • Ensure analytical datasets are accurate, reliable, and trusted, serving as a single source of truth for business, product, and stakeholders.
  • Embed data quality checks, documentation, and governance directly into analytics pipelines.
  • Partner closely with Product, Data Engineering and Analytics teams to translate business requirements into well-modeled, performant data products.
  • Mentor and support Analytics Engineers through technical guidance, design reviews, and knowledge sharing.
  • Continuously improve and modernize analytics workflows by introducing automation, tooling enhancements, and AI-assisted development where appropriate.
  • This role includes technical leadership and mentoring responsibilities for the team, including other Analytics Engineers.

As a rapidly growing company in an emerging industry, you'll have a huge impact on our product and our company. We like proactive team members and strive to have a company of self-disciplined professionals who enjoy collaboration, having fun, and of course, achieving together what others believe to be improbable. We are dedicated to treating everyone with respect and to support your professional and personal growth.

What Makes Us Great:

  • Comprehensive compensation
  • Work-life balance initiatives
  • Autonomy - we embrace personal freedom and responsibility
  • Creativity - we are open to new ideas of how we can be better
  • Growth - we want you to develop personally as well as professionally
  • Top-notch professionals who are passionate about what they do
  • People-oriented environment and supportive atmosphere

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related quantitative discipline.
  • Technical Leadership: Proven experience defining technical direction, standards, and architectural decisions within analytics engineering or curation teams.
  • Data Modeling Expertise: Deep understanding of dbt, data marts, dimensional modeling, and self-service BI enablement.
  • Data Engineering Background: 7+ years of experience in data warehousing or development; 5+ years of experience in hands-on data engineering using SQL and Python.
  • Cloud Infrastructure: Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization (Docker/Kubernetes).
  • Tooling & Orchestration: Experience with tools like dbt, Airflow, S3, REST APIs, and large-scale DWHs (Snowflake, Redshift, BigQuery, etc.).
  • Change Management: Skilled at leading cross-functional data initiatives and driving adoption of new tools and standards.
  • People Leadership: Experience mentoring and guiding distributed teams across time zones.
  • Communication: Strong written and verbal English skills with the ability to collaborate across technical and business functions.
  • Able to travel occasionally both domestically and internationally #LI-HYBRID #LI-DNP

About the company

Rush Street Interactive (NYSE: RSI) is a market leader in online casino and sports betting, currently operating real-money gaming with our brands: BetRivers.com, PlaySugarHouse.com, and RushBet.co. We're building bridges between online, social and land-based gaming businesses to create amazing, integrated experiences that keep players in the game.

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