Job VC
Senior Data Engineer
Technologies
Description
We are seeking a highly skilled
Senior Data Engineer
to design, build, and maintain scalable data infrastructure and pipelines. In this role, you will be responsible for enabling reliable data processing, ensuring high data quality, and supporting analytical and business intelligence needs across the organization. You will work with large-scale distributed systems, modern data platforms, and both batch and real-time data processing frameworks.
Key Responsibilities:
Design, develop, and maintain robust
ETL/ELT data pipelines
Build and optimize
scalable data processing systems
(batch and streaming)
Architect and manage
data lakes, data warehouses, and data marts
Develop data transformations using
SQL, Python, and Apache Spark (PySpark)
Integrate data from various sources (databases, APIs, streaming systems)
Ensure
data quality, integrity, and consistency
through validation and monitoring
Optimize performance of data pipelines (partitioning, indexing, query tuning)
Implement and maintain
workflow orchestration
(e.g., Apache Airflow)
Collaborate with cross-functional teams (Data Analysts, Data Scientists, Backend Engineers)
Support and contribute to
CI/CD pipelines
for data workflows
Document data architecture, processes, and standards
Required Qualifications
Technical Skills:
4+ years of professional experience as a Data Engineer or in a similar role
Strong proficiency in
SQL
(e.g., PostgreSQL, Snowflake, BigQuery, Redshift)
Hands-on experience with
Apache Spark / PySpark
Solid understanding of
data modeling
(normalized and dimensional models)
Experience designing and implementing
ETL/ELT pipelines
Experience with
cloud platforms
(AWS, GCP, or Azure)
Experience with:
Kubernetes
Containerization tools (Docker)
Version control systems (Git)
Nice to Have:
Experience with
stream processing
(e.g., Apache Kafka, Kinesis, Flink)
Knowledge of
modern data stack tools
(e.g., dbt, Delta Lake, Iceberg)
Experience with
data governance and lineage tools
Exposure to infrastructure as code (e.g., Terraform)
What we offer:
Paid vacation and sick leaves
Competitive salary
Flexible work schedule
Career growth
Corporate celebrating and presents
Corporate English courses
Office/hybrid work in Ternopil or opportunity for remote work
Coffee, tea, fruits, and cookies
in the office
Senior Data Engineer
to design, build, and maintain scalable data infrastructure and pipelines. In this role, you will be responsible for enabling reliable data processing, ensuring high data quality, and supporting analytical and business intelligence needs across the organization. You will work with large-scale distributed systems, modern data platforms, and both batch and real-time data processing frameworks.
Key Responsibilities:
Design, develop, and maintain robust
ETL/ELT data pipelines
Build and optimize
scalable data processing systems
(batch and streaming)
Architect and manage
data lakes, data warehouses, and data marts
Develop data transformations using
SQL, Python, and Apache Spark (PySpark)
Integrate data from various sources (databases, APIs, streaming systems)
Ensure
data quality, integrity, and consistency
through validation and monitoring
Optimize performance of data pipelines (partitioning, indexing, query tuning)
Implement and maintain
workflow orchestration
(e.g., Apache Airflow)
Collaborate with cross-functional teams (Data Analysts, Data Scientists, Backend Engineers)
Support and contribute to
CI/CD pipelines
for data workflows
Document data architecture, processes, and standards
Required Qualifications
Technical Skills:
4+ years of professional experience as a Data Engineer or in a similar role
Strong proficiency in
SQL
(e.g., PostgreSQL, Snowflake, BigQuery, Redshift)
Hands-on experience with
Apache Spark / PySpark
Solid understanding of
data modeling
(normalized and dimensional models)
Experience designing and implementing
ETL/ELT pipelines
Experience with
cloud platforms
(AWS, GCP, or Azure)
Experience with:
Kubernetes
Containerization tools (Docker)
Version control systems (Git)
Nice to Have:
Experience with
stream processing
(e.g., Apache Kafka, Kinesis, Flink)
Knowledge of
modern data stack tools
(e.g., dbt, Delta Lake, Iceberg)
Experience with
data governance and lineage tools
Exposure to infrastructure as code (e.g., Terraform)
What we offer:
Paid vacation and sick leaves
Competitive salary
Flexible work schedule
Career growth
Corporate celebrating and presents
Corporate English courses
Office/hybrid work in Ternopil or opportunity for remote work
Coffee, tea, fruits, and cookies
in the office