DataOps Engineer {job offer}

CZ - Prague
Analysis

Description

Design, build and optimize data pipelines to facilitate the extraction of data from multiple sources
Be first level support for end user’s requests when dealing with data pipeline issues
Develop ETL/ELT (batch/stream) from multiple sources using Spark and/or Kafka
Operate the data pipelines to ensure key SLAs are managed across a wide range of producers and consumers
Support various components of the data pipelines, including ingestion, validation, cleansing and curation
Promote data collaboration, orchestration, quality, security, access, and ease of use
Gather data requirements from analytics and business departments
Write and maintain operational and technical documentation and perform tasks in Agile methodology

Hands on experience with cloud native technologies, Azure/GCP
Direct experience in building data pipelines such as Data Factory, Data Fusion, or Apache Airflow
Understanding of wide range of big data technologies and data architecture
Familiarity with data platforms and technologies such as Kafka, Delta Lake, Spark; Databricks is a plus
Demonstrated experience in one or more programming languages, preferably Python
Good knowledge of CI/CD and version control tools such as Jenkins and GitHub Actions
Experience with monitoring tools like Prometheus, Grafana, ELK stack is a plus
Ability to bring both engineering and operational (DevOps) mindset to the role
Strong team player willing to cooperate with colleagues across office locations and functions
Very strong English language skills are a must