DataOps Engineer
TLDR
Design and maintain scalable data systems, focusing on automation and efficiency in data pipelines to ensure accurate and accessible data for analytics and business needs.
- Design, develop, and maintain batch and streaming data pipelines from multiple source systems
- Implement ETL/ELT processes to ingest, transform, and model data for analytics and downstream consumers
- Build and optimize data models, tables, and views in cloud data warehouses or lakehouses
- Enforce data quality, validation, and schema management across pipelines
- Optimize pipeline performance, scalability, and cost efficiency
- Collaborate with analytics and data science teams to support reporting, dashboards, and ML workloads
- Apply DataOps best practices including CI/CD for data pipelines, automated testing, and version control
- Monitor pipeline health, data freshness, and SLAs using observability and alerting tools
- Automate operational tasks such as deployments, backfills, schema evolution, and rollbacks
- Manage and improve production reliability of data systems, including on-call support and incident response
- Implement and maintain infrastructure and orchestration for data workflows
- Improve transparency and trust in data through metadata, lineage, and documentation
- Partner with platform teams on infrastructure as code, security, and access management
- 3+ years of experience in Data Engineering, DataOps, or a closely related role.
- Strong hands-on experience building and maintaining production data pipelines.
- Proficiency with Python.
- Experience with cloud data platforms (Azure, AWS, or GCP).
- Familiarity with workflow orchestration tools (e.g., Airflow, Databricks Workflows, Prefect, Dagster).
- Experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI, etc.).
- Solid understanding of data reliability, monitoring, logging, and alerting.
- Experience with Databricks, Spark, Snowflake, BigQuery, or similar platforms.
- Knowledge of streaming technologies (Kafka, Event Hubs, Spark Streaming, Flink).
- Familiarity with data quality and observability tools (e.g., Great Expectations, Monte Carlo, OpenMetadata).
- Experience with Infrastructure as Code (Terraform, ARM, CloudFormation).
- Understanding of data governance, security, and compliance practices.
Benefits
Flexible Work Hours
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Varonis builds advanced data security solutions that empower organizations to detect insider threats and ensure secure data access. Targeting enterprises navigating complex data environments, their cloud-native Data Security Platform automates threat detection and data classification, providing peace of mind in a landscape where data protection is paramount.
- Founded
- Founded 2005
- Employees
- 500+ employees
- Industry
- Internet Software & Services