Data Engineer

As a Senior Data Engineer, you'll be joining a scale-up environment where adaptability and problem-solving are key. This role is essential in designing, building, and optimizing our data architecture to support evolving business needs. With expertise in data pipeline stacks (open-source & AWS) and ClickHouse, you’ll focus on developing scalable, high-performance solutions. Collaborating closely with engineering teams, you’ll implement robust data pipelines that ensure efficiency, reliability, and alignment with business objectives. If you're looking for a role where you can make a real impact, we’d love to hear from you. 

Key Responsibilities: 

• Data pipeline Design: Robust design experience in follow and implement scalable, high-performance data architectures using AWS services and ClickHouse (or equivalent OLAP databases). 

• Data Pipeline Development: Design, build, and maintain robust ETL/ELT pipelines that efficiently handle large-scale data ingestion, transformation, and storage. 

• Cloud Infrastructure: Combine open-source data stack and AWS technologies to build and optimize data workflows. 

• Data Governance & Quality: Ensure data accuracy and consistency through best practices in data governance, lineage, and monitoring. 

• Performance Optimization: Optimize data storage, retrieval, and processing to support high-performance analytical workloads using partitioning, indexing, and query optimization techniques. 

• Collaboration & Leadership: Work closely with data scientists, analysts, and software engineers to understand requirements and deliver data-driven solutions, mentoring junior engineers. 

• Automation & CI/CD: Implement automated data pipeline deployment and monitoring strategies. 

Requirements

Requirements:

• 5+ years of experience in data engineering with solid experience on open-source data stack, and cloud native experiences. 

• Expertise in ClickHouse, or similar OLAP databases is a plus. 

• Strong experience in designing and architecting large-scale data systems. 

• Proficiency in programming languages like Python, or productivity libraries scripting languages for data processing and pipeline development. 

• Deep understanding of ETL/ELT processes, data modeling (Star Schema, Snowflake Schema), and data warehousing. 

• Experience with orchestration tools such as Apache Airflow, Step Functions, or Dragster. 

• Hands-on experience with infrastructure-as-code (Terraform, CloudFormation, CDK) is a plus 

• Strong problem-solving skills and ability to work in a fast-paced environment. 

• Knowledge of SQL query performance tuning, materialized views, and sharding strategies for large datasets. 

• Familiarity with containerization and serverless computing (Docker, Kubernetes). 

• Experience with monitoring and observability tools such as Prometheus, Grafana, AWS CloudWatch. 

Benefits

Here's a glimpse of what's waiting for you:   

• A competitive salary package that rewards your hard work.  
• 25 paid vacation days. And if that's not enough, you can purchase up to 10 more.  
• A world of growth and development opportunities to enhance your skills. You'll have unlimited access to our treasure trove of GoodHabitz resources and MyAcademy .  
• Access to mental coaching through our partner, OpenUp, to keep your mind in top shape.  
• An annual do-good-day, fully paid, so you can contribute to a cause you're passionate about.   
• Travel and expense reimbursement because we've got your journey covered.   
• Pension and disability insurance, securing your financial well-being in the long run.   
• A hybrid way of working .   
• Working in a company that welcomes artificial intelligence and uses it to improve internal processes and push AI-powered features quickly .  
• MacBook Pro.