Middle Data Engineer for Data Platform Team

What You’ll Be Driving:

• Working with large datasets (100+ TB) with updates at least hourly;
• Developing and supporting ETL/ELT processes across multiple data sources;
• Building and maintaining data warehouses and data marts on AWS (S3, Athena, Redshift), GCP (Cloud Storage, BigQuery), and PostgreSQL;
• Designing and implementing RESTful APIs (Aiohttp, Flask, FastAPI) for internal and external data consumption;
• Collecting and processing data from Kafka, Google Analytics, Firebase, Appsflyer, Cloudflare, and other third-party applications;
• Designing and maintaining a centralized data catalog with well-validated and documented data models;
• Automating data quality and integrity tests to ensure high data reliability;
• Developing and integrating semantic layers to standardize data access across teams;
• Creating and maintaining comprehensive project documentation;
• Collaborating with cross-functional teams to understand business requirements and translate them into scalable data solutions;
• Driving continuous improvement in data engineering processes, tools, and best practices;
• Monitoring data pipelines, resolving incidents, and optimizing performance.

What Makes You a GR8 Fit:

• Minimum of 2+ years of experience in Python / Data Engineering;
• Hands-on experience with ETL, Data Warehousing, and relational databases (PostgreSQL, Microsoft SQL Server, etc.);
• Experience with job scheduling and task queues;
• Familiarity with cloud providers: AWS (S3, Athena, Redshift), GCP (Cloud Storage, BigQuery), or similar;
• Proficiency in Linux and containerization (Docker);
• Experience with BDD, TDD, or unit testing frameworks;
• Extensive knowledge of software design best practices and design patterns;
• Solid Computer Science fundamentals and database theory (types, pros/cons);
• Experience in performance tuning of ETL jobs, SQL queries, partitioning, and indexing;
• Hands-on experience with version control systems (git) and CI/CD pipelines;
• Familiarity with web/mobile application data sources is a plus;
• Knowledge or experience with Kubernetes, Apache Airflow, DBT, NoSQL databases (MongoDB, Elasticsearch, Redis), Kafka ecosystem, IaC tools (Terraform, Ansible), Salesforce platforms, and Graph
• databases (Neo4j, AgensGraph) is a plus;
• Experience in near real-time data processing and data visualization tools (Tableau, PowerBI, Metabase, Grafana, Kibana, Apache Superset) is a plus;
• Strong problem-solving, analytical, and data-driven decision-making skills;
• Excellent communication skills, with the ability to collaborate across technical and non-technical teams;
• Intermediate English or higher.