Lead Data Architect

3 weeks ago


Remote, Czech Republic AVENGA Full time
Job Description

We are seeking an experienced Lead Data Architect to join our team at Avenga.

About the Role

In this position, you will be responsible for designing and implementing large-scale data pipelines using cloud technologies such as Airflow, Glue, and Dataflow. You will work closely with cross-functional teams to ensure seamless integration of data architecture concepts into our product offerings.

Key Responsibilities
  • Design and implement scalable data architectures using cloud technologies.
  • Develop and maintain data pipelines to extract, transform, and load data from various sources.
  • Collaborate with data engineers to ensure high-quality data delivery.
  • Work with stakeholders to understand business requirements and design data solutions that meet their needs.
  • Stay up-to-date with industry trends and emerging technologies in data engineering and architecture.
Requirements
  • 4+ years of experience working with programming languages focused on data pipelines (e.g., Python or R).
  • 4+ years of experience working with SQL.
  • 3+ years of experience in data pipelines maintenance.
  • 3+ years of experience with different types of storage (filesystem, relational, MPP, NoSQL) and working with various kinds of data (structured, unstructured, metrics, logs, etc.).
  • 3+ years of experience in working in data architecture concepts (in any of the following areas: data modeling, metadata management, workflow management, ETL/ELT, real-time streaming, data quality, distributed systems).
  • 3+ years of cloud technologies with emphasis on data pipelines (Airflow, Glue, Dataflow - but also other smart solutions for handling data in the cloud - Elastic, Redshift, BigQuery, Lambda, S3, EBS, etc.).
  • 1+ years of experience in Java and/or Scala.
  • Very good knowledge of relational databases (optional).
  • Very good knowledge of data serialization languages such as JSON, XML, YAML.
  • Excellent knowledge of Git, Gitflow, and DevOps tools (e.g., Docker, Bamboo, Jenkins, Terraform).
  • Capability to conduct performance analysis, troubleshooting, and remediation (optional).
  • Excellent knowledge of Unix.
  • Pharma data formats is a big plus (SDTM).
Requirements Continued
  • Python.
  • SQL.
  • Data modeling.
  • ETL.
  • Redshift.
  • AWS Lambda.
  • AWS S3.
  • Git.
  • DynamoDB.
  • Snowflake.
Benefits
  • Sport subscription.
  • Training budget.
  • Private healthcare.
  • International projects.


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