Data Engineer/ Tech Lead

1 day ago

Remote, Czech Republic Link Group Full time
  • Proven experience in data engineering with a strong focus on streaming.
  • Strong expertise in Confluent Kafka and Spark Structured Streaming.
  • Hands-on experience with CDC and real-time data extraction.
  • Solid programming background: Python, SQL, Bash, Node.js, Linux/Unix Shell.
  • Strong knowledge of data engineering lifecycle: versioning, release management, deployment, agile delivery.
  • Experience with cloud-native & DevOps tools: GitHub Actions, Terraform, Kubernetes.
  • Previous experience in a technical leadership role (designing solutions, guiding teams, mentoring).
Nice to Have
  • Multi-cloud exposure (AWS, Azure, GCP).
  • Knowledge of wider big data & analytics platforms (Databricks, Snowflake, Delta Lake).
  • Experience in stakeholder management and solution consulting.

We are seeking a Data Engineer / Tech Lead with a strong background in real-time data streaming to lead the design and delivery of cutting-edge streaming solutions. This role combines hands-on engineering with technical leadership – you will both architect scalable data streaming systems and guide a team to successful implementation.

,[Act as technical lead for projects with a strong streaming/data engineering focus., Design end-to-end architectures for data streaming use cases, ensuring scalability, reliability, and performance., Implement Change Data Capture (CDC) and other real-time extraction mechanisms., Drive adoption and best practices in Confluent Kafka and Spark Structured Streaming., Lead the development of streaming pipelines using Python, SQL, Bash, Node.js, and Linux/Unix Shell., Oversee code quality, versioning, release management, and CI/CD processes., Guide the team in applying DevOps and cloud-native tools: GitHub Actions, Terraform, Kubernetes, etc., Collaborate with business stakeholders, data scientists, and platform teams to align streaming solutions with organizational goals., Mentor junior/mid-level engineers, fostering growth and technical excellence within the team.] Requirements: Data, Data engineering, Confluent Kafka, Spark Streaming, CDC, Real-time data extraction, Python, SQL, Bash, Node.js, Linux, Unix Shell, Data engineering lifecycle, cloud-native, GitHub Actions, Terraform, Kubernetes, AWS, Azure, GCP, Big data, Analytics platform, Databricks, Snowflake, Delta Lake

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