Data Engineer - ETL

Involved in entire development lifecycle, from brainstorming ideas to implementing elegant solutions to obtain data insights.
Gather requirements, model and design solutions to support product analytics, business analytics and advance data science.
Design efficient and scalable data pipelines using cloud‑native and open source technologies.
Develop and improve ETL/ELT processes to ingest data from diverse sources.
Work with analysts, understand requirements, develop technical specifications for ETLs, including documentation.
Support production code to produce comprehensive and accurate datasets.
Automate deployment and monitoring of data workflows using CI/CD best practices.
Promote strategies to improve data modelling, quality and architecture.
Participate in code reviews, mentor junior engineers, and contribute to team knowledge sharing.
Document data processes, architecture, and workflows for transparency and maintainability.
Work with big data solutions, data modelling, understand the ETL pipelines and dashboard tools.

4+ years relevant industry experience in a data engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Proficiency in writing SQL queries and knowledge of cloud‑based databases like Snowflake, Redshift, BigQuery or other big data solutions.
Experience in data modelling and tools such as dbt, ETL processes, and data warehousing.
Experience with at least one of the programming languages Python, C++ or Java.
Experience with version control and code review tools such as Git.
Knowledge of latest data pipeline orchestration tools such as Airflow.
Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure‑as‑code tools (e.g., Docker, Terraform, CloudFormation).
Familiarity with data quality, data governance, and observability tools (e.g., Great Expectations, Monte Carlo).
Experience with BI and data visualization tools (e.g., Looker, Tableau, Power BI).
Experience working with product analytics solutions (Amplitude, Mixpanel).
Experience working on mobile attribution solutions (Appsflyer, Singular).
Experience working on a mobile game or a mobile app, ideally from early stages of the product life cycle.
Experience working in an Agile development environment and familiar with process management tools such as JIRA, Target process, Trello or similar.

Familiarity with data security, privacy, and compliance frameworks.
Exposure to machine learning pipelines, MLOps, or AI‑driven data products.
Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark.
Exposure to AI/ML concepts and collaboration with data science or AI teams.
Experience integrating data solutions with AI/ML platforms or supporting AI‑driven analytics.

Mid‑Senior level

Full‑time

Engineering and Information Technology

Computer Games

See also