Question
5-10

Data Engineer - BI Team

4/26/2026

You will lead the design and development of scalable data warehouse solutions and build core data infrastructure as a product. Additionally, you will manage end-to-end ELT/ETL processes and implement robust data quality and governance frameworks.

Working Hours

40 hours/week

Company Size

51-200 employees

Language

English

Visa Sponsorship

No

About The Company
Built on a robust ITSM platform, SysAid’s Agentic AI adds a powerful new operational layer to IT—automating the repetitive, time-consuming work that keeps teams stuck in reactive mode. AI Agents take the first action, so IT pros step in only when truly needed. The result? A team free to focus on optimization, innovation, and bigger challenges. Go live in weeks with fast onboarding, no heavy migrations, and zero steep learning curves. SysAid’s AI is purpose-built for IT, with security and governance built in. And with award-winning support, you’re set up for success. ITSM run by AI—and you. 100X more impactful.
About the Role

We are at a pivotal stage in building and scaling our data domain, and we are looking for a Data Engineer to join our growing BI team. This role goes beyond building pipelines. You will help shape our data platform as a shared product - supporting analytics, reporting, and decision-making across key company data domains such as Product, Sales, HR, and others. Your work will directly influence how stakeholders interact with data today and how the platform evolves in the years ahead.

What You’ll Be Doing

  • Architect & Own: Lead the design and development of scalable data warehouse and BI solutions. You will make early-stage architectural decisions and own their long-term impact.
  • Infrastructure as a Product: Build core data infrastructure and developer experiences that others rely on, ensuring high availability and system reliability.
  • End-to-End ELT/ETL: Solve complex integration problems by sourcing data from structured and unstructured sources using Rivery, Python, and optimal ETL patterns.
  • Data Quality & Governance: Implement frameworks for schema evolution, anomaly detection, and data freshness. You will determine security models based on privacy requirements and evolve governance processes.
  • Strategic Collaboration: Partner with Engineers, Product Managers, and Data Analysts to conceptualize data needs and represent key insights in a meaningful way.
  • Optimization: Assist in owning production processes, optimizing complex code through advanced algorithmic concepts to manage operational cost-benefit tradeoffs.

What You’ll Bring (Requirements)

  • Experience: 5+ years of experience in Data Engineering, Infrastructure, or Platform Engineering (ideally in organizations operating at a meaningful scale).
  • Technical Mastery: 5+ years of hands-on experience with Python and SQL. Deep proficiency in data modeling (Star/Snowflake schema) and DWH methodologies.
  • Cloud & Tools: Proven experience with Snowflake and AWS. Familiarity with Rivery or similar orchestration tools (like DBT) is a major advantage.
  • Production-First Mindset: Track record of leading data initiatives end-to-end from design and building to shipping and operating production flows.
  • Analytical Rigor: Ability to triage issues, resolve data quality problems, and design systems that handle system complexity with ease.
  • Education: Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field.

Why Join Us?

  • Impact: You are joining at a stage where you can design the architecture "from scratch."
  • Fast-Paced Culture: We operate in a "move fast and break things" environment. Perfect for those who love high autonomy and rapid iteration.

Requirements

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Key Skills
PythonSQLData EngineeringSnowflakeAWSData ModelingETLELTData WarehousingRiveryData GovernanceInfrastructure EngineeringSystem ReliabilitySchema EvolutionAnomaly Detection
Categories
Data & AnalyticsSoftwareTechnologyEngineering
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