Simulmedia is seeking a senior Data Engineer to join the Data Services team. The role involves designing, building, and operating large-scale data pipelines and data models that support the company's TV and streaming advertising platform. Responsibilities include developing batch data pipelines, modeling complex data, operating workloads on Databricks/Spark/Delta and Redshift, orchestrating pipelines with Airflow, building Python services and REST APIs, optimizing performance and cost, monitoring production pipelines, and collaborating cross-functionally. Required qualifications include a bachelor's degree or equivalent experience, 7+ years as a data engineer, proficiency in Python and SQL, experience with distributed data processing platforms (preferably Spark/Databricks), columnar data warehouses, workflow orchestration tools, REST API development, AWS, Docker, and engineering best practices. The position is full-time, hybrid remote with offices in Kyiv and Lviv, Ukraine, and requires working hours aligned with US teams (11:00 AM - 8:00 PM EEST).
What you'll do
Design and build batch data pipelines that ingest, validate and transform multi-billion-row datasets from external data providers and internal systems
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Model complex real-world data: dimensional models, reference data, and temporal data whose attributes change over time (e.g. slowly changing dimensions), and evolve those models safely as upstream sources change their schemas and semantics
Develop and operate workloads on our lakehouse platform (Databricks / Spark / Delta) and our data warehouse (Redshift), including migrating existing pipelines from the warehouse to the lakehouse
Orchestrate pipelines with Airflow: scheduling, dependencies, retries, backfills and alerting
Prove correctness, not just completion: design parity checks and reconciliation queries when replacing an existing pipeline, run large historical backfills, and investigate data discrepancies down to the row level
Build and maintain Python services and REST APIs that serve data to internal products
Optimize for performance and cost: query tuning, table design, workload management and right-sizing compute
Own what you ship: monitor production pipelines, participate in incident triage and root-cause analysis, and harden systems so the same failure does not happen twice
Collaborate cross-functionally with product managers, data scientists and stakeholders across the company to deliver on product roadmap
Work within an Agile team that releases cutting-edge new features regularly
Take a high degree of ownership and freedom to experiment with new technologies to improve our software
Requirements
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
7+ years of work experience as a data engineer
Proficiency in Python and using it as the primary development language in recent years
Expert-level SQL: comfortable writing, reading and tuning complex analytical queries against very large tables, and debugging why two result sets disagree
Hands-on experience with a distributed data processing platform (Spark/Databricks strongly preferred; EMR, Snowflake or BigQuery also relevant) and with a columnar data warehouse (Redshift, Snowflake, BigQuery, ClickHouse, etc)
Ability to design complex data models: normalized, dimensional and temporal (slowly changing dimensions, effective-dated records, point-in-time correctness)
Experience with workflow orchestration tools (Airflow or similar): building DAGs, managing dependencies and running backfills
Experience integrating third-party data feeds: handling schema drift, late or missing deliveries, vendor data-quality defects and versioned reference data
Experience building REST services in Python (FastAPI, Flask, etc)
Experience developing, maintaining, and debugging problems in large server-side code bases
Working knowledge of AWS (S3, IAM, ECS or similar compute) and Docker
Good knowledge of engineering best practices and testing (unit test, integration test, code review, CI/CD)
The desire to take a high level of ownership of the things you work on
Ability to learn new things quickly, maintain a high bar for quality, and be pragmatic
Must be able to communicate with U.S based teams
Ability to communicate effectively with the U.S.-based teams and work 11:00 AM — 8:00 PM EEST (11:00 - 20:00)
Experience with Delta Lake / medallion lakehouse architectures is a plus
Experience migrating legacy pipelines between platforms with strict parity requirements is a plus
Experience with advertising, media or measurement industry data is a plus
