1 день назад
Senior Data Engineer (Databricks/Snowflake)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (Databricks/Snowflake): Build and operate scalable data warehouses, ETL/ELT pipelines, dimensional models, and analytical tools with an accent on cloud data platforms, performance optimization, and data quality. Focus on designing reliable data infrastructure, automating database operations, implementing governance and access controls, and transforming complex datasets into actionable business insights.
Location: Ukraine; flexible work formats are available, including remote, hybrid, and onsite options.
Company
is a software engineering company delivering data, analytics, and AI solutions for clients across multiple industries.
What you will do
- Develop, operate, test, and optimize data warehouses, including ETL/ELT pipelines, dimensional tables, cubes, and database performance.
- Own the full backend development lifecycle for the data warehouse.
- Redesign infrastructure for scalability, optimize data delivery, and automate manual processes.
- Define data retention policies and implement automated database updates and vulnerability fixes.
- Build analytical tools that transform complex datasets into actionable business insights.
- Select and integrate monitoring, alerting, and database performance management tools.
Requirements
- 5+ years of experience or 5+ completed projects in data engineering.
- Advanced SQL, query optimization, relational database design, and performance tuning.
- Python for data engineering and automation.
- Experience with Snowflake or Databricks and AWS or Azure cloud services.
- DBT, ETL/ELT pipeline development, Apache Spark, and workflow orchestration with Apache Airflow, Dagster, or a comparable tool.
- Experience with data warehousing, dimensional modeling, Git, CI/CD, data governance, data quality, lineage, observability, security, and access control.
Nice to have
- Apache Kafka, Apache Flink, Apache Beam, Terraform, Kubernetes, or Docker.
- Apache Iceberg, Delta Lake, Apache Hudi, or real-time and event-driven architectures.
- AWS Glue, Amazon MWAA, Azure Data Factory, Data Mesh, or Data Product experience.
- Machine learning data pipelines, feature stores, AI development, streaming analytics, or CDC solutions such as Debezium.
Culture & Benefits
- Flexible remote, hybrid, and onsite work options with equipment and secure access support.
- Vacation according to local legislation and paid sick leave, including 10 days without a doctor's note.
- Health insurance support for employees and their loved ones.
- Time off for state holidays according to the official local calendar.
- Support for professional development, including IT certification costs, mentoring, and access to learning platforms.
- Corporate events, mental health support, and practical workplace assistance.
Hiring process
- CV review followed by an HR interview.
- Communication and technical assessments covering English and relevant technologies.
- Project team meeting and possible client interview preparation.
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