Lead Data Architect
3 weeks ago
We are seeking an experienced Lead Data Architect to join our team at Avenga.
About the RoleIn 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.
- 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).
- Python.
- SQL.
- Data modeling.
- ETL.
- Redshift.
- AWS Lambda.
- AWS S3.
- Git.
- DynamoDB.
- Snowflake.
- Sport subscription.
- Training budget.
- Private healthcare.
- International projects.
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