Data Engineer - Data Warehouse & Analytics
Lensa · Budapest, HU ·
- Category
- Data engineering
- Experience
- 5+ years
Lensa · Budapest, HU ·
is one of the biggest recruitment and career platforms on the United States market, with 20+ million registered users. The company is founded and managed by Hungarian professionals who introduced and developed the well known .
Our product represents the future of career development: job search that puts people first while reducing the time and cost of talent acquisition. Using machine learning, we instantly match job seekers with positions that fit their skills, career goals and personalities. We make the world better, by placing every job seeker in the best possible positions for them. We are proud of our 4.3+ Trustpilot score!
Lensa is dedicated to achieving its business goals with cutting-edge, scalable technologies. With teams in multiple U.S. locations and a talented crew of developers, product managers and data scientists in Budapest, we are working every day to share our transformative career technology with the world.
If you're interested in joining our journey and contributing to our success as part of our dynamic international team, we look forward to receiving your application!
About the role
Lensa's data warehouse is the analytical backbone of the company — a Redshift warehouse of roughly 2,000 tables, with around 400 tables feeding the reporting layer, plus product analytics and ML training data. As a Data Engineer on this team, you will design intuitive data models and reliable transformation workflows that let stakeholders across the company leverage data effectively. A major part of the role is modernizing our warehouse architecture: rebuilding legacy ETL as layered, tested, documented models — with dbt as the target framework.
We are looking for an engineer who is passionate about intuitive data models, expert in SQL, and experienced in evolving a warehouse without disrupting the business that runs on it.
What You'll Do
Design and implement dimensional data models (star schemas, slowly changing dimensions) serving reporting, analytics, and ML use cases
Build, optimize, and maintain robust ELT workflows feeding the data warehouse and downstream analytical layers
Refactor legacy ETL into layered, tested, documented transformation models
Own warehouse performance and cost: distribution and sort key design, workload management, materialization strategy
Establish data quality as code — automated tests, freshness checks, and contracts with upstream data producers
Document models, metric definitions, and naming conventions so analysts can self-serve
Work with Data Scientists, Analysts to translate business requirements into scalable data models
Identify technical risks in the analytical layer and drive improvements in reliability and design
What You Bring
5+ years in data engineering or analytics engineering with a data warehouse at the center of your work
Expert SQL: window functions, CTE-heavy transformations, query plan analysis, and performance tuning on an MPP warehouse (Redshift, Snowflake, or BigQuery)
Strong dimensional modeling fundamentals and demonstrable data intuition
Experience with dbt or a comparable transformation framework
Experience maintaining or migrating a legacy warehouse in production
Working Python for pipeline tooling and automation
Excellent communication skills with both technical and non-technical stakeholders
Solid communication skills in English
Bonus Points
A dbt migration you've driven — from stored procedures, hand-rolled ETL, or another framework
Data governance, metadata management, lineage, and data quality frameworks
Exposure to the lake side: S3, Glue Data Catalog, Iceberg, Spark
Experience designing analytical layers or building a warehouse architecture from scratch
What We Offer
Flexible working hours with home office opportunity
Medicover health insurance
Company lunch every day in the office
In-house gym in the office
Exciting programs and team-building events
Recreation room with darts, ping pong, foosball, XBox, and other games
Modern and fancy office in Buda close to Széll Kálmán tér
If you prefer to work in a startup environment but still a stable, fast growing company, and you’re interested in the role please do not hesitate to apply!