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Data Engineer
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Über
We're looking for a mid-level Data Engineer & DBA to join our data platform team. You'll build and maintain scalable data pipelines while ensuring our databases are reliable, secure, and high-performing. You'll work closely with analysts, engineers, and product teams to deliver clean and timely data. What You'll Do Design, build and maintain ETL/ELT pipelines across multiple systems Design and optimize data models in PostgreSQL, MongoDB, and Amazon Redshift Develop and manage data workflows using AWS (S3, Glue, Lambda, Step Functions, Kinesis) Administer and maintain database environments across development, staging, and production Monitor data pipelines and databases, troubleshoot issues, and implement alerts Optimize query performance, indexes, and configurations across relational and NoSQL systems Manage database provisioning, upgrades, backups, and disaster recovery (RDS, MongoDB, Redshift) Ensure database security, including access control, encryption, and role management Plan capacity and scale systems to support growing data needs Define and enforce data retention and archival policies Collaborate with analytics and product teams to support reporting and data needs Document data pipelines, database processes, and operational procedures Participate in code reviews and follow engineering best practices What We're Looking For Core Skills & Experience 3–5 years of experience in data engineering, database administration, or similar roles Strong experience with PostgreSQL, MongoDB, and Amazon Redshift Solid SQL skills for both transactional and analytical workloads Experience with AWS data and database services (S3, Glue, Lambda, RDS, Redshift, etc.) Proficiency in Python or another scripting language Experience with workflow orchestration tools (Airflow, Step Functions, etc.) Hands-on database administration experience, including: MongoDB (replica sets, sharding, indexing, backups) Redshift (cluster management, query tuning, WLM, snapshots) PostgreSQL (replication, performance tuning, connection pooling) Familiarity with monitoring tools (CloudWatch, pgBadger, MongoDB Atlas, etc.) Understanding of database security (encryption, auditing, least-privilege access) Nice to Have Experience with Kafka or Kinesis (streaming data) Familiarity with dbt for data transformation Knowledge of data lake/lakehouse architectures (Delta Lake, AWS Lake Formation) Experience with Terraform or CloudFormation CI/CD experience for data pipelines Basic DevOps skills Skills & Attributes Strong problem-solving and analytical skills Ability to translate business needs into data solutions Comfortable working in a fast-paced, collaborative environment Clear communicator with both technical and non-technical audiences Self-motivated with a focus on clean, maintainable code Education Bachelor's degree in Computer Science, Engineering, or a related field — or equivalent experience.
Sprachkenntnisse
- English
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