Robotics Technologies is hiring a Senior Data Engineer for an onsite role in Atlanta, GA. In this position, you will build and operate production-grade batch and streaming data pipelines, integrate lakehouse layers with analytics systems, and help ensure data quality, monitoring, and reliable delivery to downstream teams.
What you’ll be building
- Production pipelines that ingest and transform data from SQL Server, cloud applications, device and event streams, Customer Relationship Management systems, and third-party sources.
- Lakehouse data layers spanning landing, raw, conformed, and consumption zones using Apache Iceberg and Trino.
- Dimensional and analytical models for entities such as buildings, tenants, credentials, devices, and people.
- Automated data-quality checks, pipeline monitoring, lineage, freshness alerts, and operational dashboards.
- Integrations between the lakehouse and Snowflake, including Iceberg-backed/external tables, secure sharing, and downstream data contracts.
How the work runs in production
- Implement robust handling for Change Data Capture, late-arriving data, retries, backfills, replay, schema evolution, and data reconciliation.
- Troubleshoot and resolve production issues including pipeline failures, performance bottlenecks, and data-quality problems.
- Optimize SQL queries, storage layouts, partitioning and clustering, compute utilization, and overall platform cost.
- Apply security controls such as role-based access, row/column-level security, masking, and protection of sensitive data.
Engineering and collaboration
- Build and maintain CI/CD pipelines, automated testing, infrastructure-as-code, and environment promotion processes.
- Support production operations including incident resolution, Root Cause Analysis, deployments, and on-call activities.
- Partner with Product, Application Engineering, Quality Assurance, DevOps/Site Reliability Engineering, Analytics, and globally distributed engineering teams.
- Contribute to technical design decisions and documentation while staying hands-on in implementation and production delivery.
Requirements
- 6+ years of hands-on experience in data engineering, data warehousing, or data platform development.
- Strong production experience building and supporting end-to-end data pipelines.
- Expert SQL, including complex queries, query-plan analysis, and performance tuning.
- Strong development skills in Python, Java, or Scala.
- Hands-on experience with Apache Iceberg, Delta Lake, or Apache Hudi.
- Experience with distributed query technologies such as Trino, Presto, or Spark SQL.
- Hands-on Snowflake experience, including data modeling, performance optimization, external/Iceberg tables, secure data sharing, or access management.
- Experience with streaming and Change Data Capture technologies such as Apache Flink, Kafka, Spark Structured Streaming, or Debezium.
- Strong understanding of dimensional modeling, data quality, schema evolution, and data contracts.
- Experience with Kubernetes, containers, CI/CD, and infrastructure-as-code.
- Experience implementing monitoring, alerting, lineage, reconciliation, and operational support for production data platforms.
- Ability to independently troubleshoot complex production issues and drive them through resolution.
Preferred qualifications
- Experience with multi-tenant SaaS data platforms and customer data isolation.
- Experience integrating open lakehouse platforms with Snowflake.
- Azure cloud experience.
- Experience with Airflow, Dagster, dbt, Power BI, Looker, or Superset.
- Experience with data governance, cataloging, masking, and access-control frameworks.
- Exposure to Internet of Things/device telemetry, physical security, commercial real estate, or property technology.
- Experience using AI-assisted engineering tools to accelerate data development.
Technologies: SQL Server, Apache Flink, Kafka, Change Data Capture, SQL, Python, Java, Scala, Apache Iceberg, Trino, Snowflake, Apache Hudi, Delta Lake, Presto, Spark SQL, Spark Structured Streaming, Debezium, Kubernetes, Continuous Integration, Continuous Deployment, Infrastructure-as-code, Row/column-level security.
