Senior Data Engineer

Robotics Technologies is seeking a Senior Data Engineer to design, build, and operate production-grade data infrastructure in Atlanta, GA. The role focuses on reliable batch and streaming pipelines, lakehouse integrations, and the operational practices needed to keep data trustworthy and available.

In this position, you will partner across Product, Application Engineering, Quality Assurance, DevOps/Site Reliability Engineering, Analytics, and distributed engineering teams to deliver hands-on implementation and production support.

What you’ll do

• Build and run production-grade batch and streaming data pipelines spanning SQL Server, cloud applications, device and event streams, CRM systems, and third-party sources.
• Develop ingestion, transformation, and enrichment workflows using Apache Flink, Kafka, Change Data Capture, SQL, and Python/Java/Scala.
• Implement lakehouse data layers across landing, raw, conformed, and consumption zones with Apache Iceberg and Trino.
• Create dimensional and analytical models for entities including buildings, tenants, credentials, devices, and people.
• Handle Change Data Capture and real-world streaming complexities such as late-arriving data, retries, backfills, replay, schema evolution, and data reconciliation.
• Build and maintain integrations between the lakehouse and Snowflake, including Iceberg-backed or external tables, secure sharing, and downstream data contracts.
• Implement automated data-quality checks, pipeline monitoring, lineage, freshness alerts, and operational dashboards.
• Troubleshoot production data issues, pipeline failures, performance bottlenecks, and data-quality problems.
• Optimize SQL query performance and platform cost through storage layout, partitioning, clustering, and compute utilization improvements.
• Apply security controls such as role-based access, row and column-level security, masking, and protections for sensitive data.
• Own CI/CD for data pipelines, including automated testing, infrastructure-as-code, and environment promotion processes.
• Support production operations through incident resolution, Root Cause Analysis, deployments, and on-call activities.
• Contribute to technical design decisions and documentation while staying primarily hands-on in 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 experience, 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 or 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.

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

Preferred qualifications

• Experience with multi-tenant Software as a Service 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 Artificial Intelligence-assisted engineering tools to accelerate data development.