The Data Engineer will build data connectors, develop functions, maintain ETL pipelines, ensure data quality, and collaborate with teams to optimize solutions.
Intetics Inc., a leading American technology company specializing in custom software application development, distributed professional teams creation, software product quality assessment, and “all-things-digital” solutions, is looking for a Middle+/Senior Data Engineer to join its innovative team.
The client is building an E2E Data Platform that collects player-level data for brands, enabling revenue tracking across multiple pages and brands. This project is designed to become the central source of truth for user journey insights — helping the company make smarter, faster, and more impactful decisions that drive both commercial growth and product innovation.
The majority of the data is collected via Web and API scraping, then processed and integrated into Snowflake and other reporting tools.
Responsibilities
- Build connectors to external partners to harvest and process data
- Develop custom functions and transformation logic
- Integrate data into Snowflake and downstream analytics/reporting platforms
- Design, build, and maintain ETL/ELT pipelines and batch/streaming workflows
- Own critical parts of the Airflow-based orchestration layer and Kafka-based event streams
- Ensure data quality, reliability, and observability across pipelines
- Build reusable data tools and frameworks for analytics and reporting use cases
- Collaborate cross-functionally with analysts, PMs, and engineers to deliver high-quality data
- Continuously improve, optimize, and challenge existing solutions
- 5+ years of experience as a Data Engineer or Software Engineer working with data infrastructure
- Strong Python skills, with hands-on experience in SQL and Snowflake
- Experience integrating data from APIs (must-have)
- Knowledge of Airflow (or similar orchestration tools) and Kafka (or similar streaming platforms)
- Solid understanding of data modeling, governance, and performance tuning in warehouse environments
- Hands-on experience with cloud-native environments (AWS preferred), including Terraform and Docker
- Ability to work independently and prioritize tasks across multiple stakeholders
Top Skills
Airflow
AWS
Docker
Kafka
Python
Snowflake
SQL
Terraform
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