Senior Data Engineer

About the project:
Data solution to gather and transform data from multiple heterogeneous systems across our client’s organization into the Azure Data Lakehouse using Databricks and ADF.
Responsibilities:
● Design complex ETL processes of various data sources in the data Lakehouse
● Build new and maintain existing data pipelines using Python to improve efficiency and latency
● Improve data quality through anomaly detection by building and working with internal tools to measure data and automatically detect changes
● Identify, design, and implement internal process improvements, including re-designing infrastructure for greater scalability, optimizing data delivery,        and automating manual processes
● Perform data modeling and improve our existing data models for analytics
● Collaborate with SMEs, architects, analysts, data scientists, and others to build solutions that integrate data from many of our enterprise data sources
● Partner with stakeholders, including data, design, product, and executive teams, and assist them with data-related technical issues

Requirements:
● 3-5 years of commercial experience in building and maintaining complex data pipelines
● Proficiency in Python and SQL
● Well-versed in the optimization of ETL processes
● Solid skills in Bash scripting
● Solid knowledge of relational SQL and NoSQL databases: PostgreSQL/Redshift/MongoDB, Snowflake
● Knowledge of job scheduling and orchestration tools (Airflow etc.)
● Good knowledge of cloud services (Azure)
● Solid expertise in data processing tools for Azure: Elasticsearch, Azure Data Factory, Databricks, Azure Synapse
● Decent knowledge of CI/CD (Docker, Jenkins, Terraform, Git)
● Good understanding of algorithms and data structures
● Experience in the schema and dimensional data design
● Excellent communication skills, both written and verbal
● English level: upper intermediate+

Nice to have:
● Databricks certification
● Microsoft Azure certification