Senior Data Engineer

Quantum Technologies. LLC; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Quantum Technologies LLC in Atlanta, GA is seeking an experienced Data Engineer to design and operate production-grade batch and streaming data pipelines across SQL Server, cloud apps, device streams, and CRM sources.

You will implement lakehouse layers with Apache Iceberg and Trino, build dimensional models for key entities, and ensure data quality, lineage, and secure data sharing with Snowflake. Collaborate with global teams and drive CI/CD and IaC initiatives.

Qualifications

• 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.

Responsibilities

• Build and operate production-scale batch and streaming data pipelines across multiple sources.
• Develop ingestion, transformation, and enrichment pipelines using Flink, Kafka, SQL, and Python/Java/Scala.
• Implement lakehouse data layers using Iceberg and Trino across landing to consumption zones.
• Create dimensional and analytical models for buildings, tenants, credentials, devices, and people.
• Ensure data quality, reconciliation, schema evolution, and robust CDC handling.
• Integrate lakehouse with Snowflake through Iceberg-backed/external tables and secure sharing.
• Develop monitoring, lineage, freshness alerts, and operational dashboards.
• Troubleshoot production data issues, performance bottlenecks, and data quality problems.
• Optimize queries, storage layouts, partitions, and compute cost.
• Implement security controls including role-based access and data masking.
• Contribute to CI/CD pipelines, IaC, testing, and environment promotion.
• Participate in on-call, incident resolution, and root cause analysis.
• Collaborate with product, QA, DevOps, analytics, and distributed teams.

Skills

Data Engineering

SQL Proficiency

Python/Java/Scala

Apache Iceberg

Trino/Presto

Snowflake

Kafka

Flink

Kubernetes

Dimensional Modeling

Tools

Iceberg

Snowflake

Kafka

Airflow

Job description

• Build and operate production-grade batch and streaming data pipelines across SQL Server, cloud applications, device/event streams, Customer Relationship Management systems, and third-party sources.
• Develop ingestion, transformation, and enrichment pipelines using Apache Flink, Kafka, Change Data Capture, SQL, and Python/Java/Scala.
• Implement lakehouse data layers across landing, raw, conformed, and consumption zones using Apache Iceberg and Trino.
• Build dimensional and analytical models for entities such as buildings, tenants, credentials, devices, and people.
• Implement robust handling for Change Data Capture, late-arriving data, retries, backfills, replay, schema evolution, and data reconciliation.
• Build and maintain integration between the lakehouse and Snowflake, including Iceberg-backed/external tables, secure sharing, and downstream data contracts.
• Develop automated data-quality checks, pipeline monitoring, lineage, freshness alerts, and operational dashboards.
• Troubleshoot and resolve production data issues, pipeline failures, performance bottlenecks, and data-quality problems.
• Optimize SQL queries, storage layouts, partitioning, clustering, compute utilization, and overall platform cost.
• Implement security controls including role-based access, row/column-level security, masking, and protection of sensitive data.
• Build and maintain Continuous Integration and Continuous Deployment pipelines, automated testing, infrastructure-as-code, and environment promotion processes.
• Participate in production support, incident resolution, Root Cause Analysis, deployment, and on-call activities.
• Work closely with Product, Application Engineering, Quality Assurance, DevOps/Site Reliability Engineering, Analytics, and globally distributed engineering teams.
• Contribute to technical design decisions and documentation while remaining primarily hands-on in implementation and production delivery.

Required Skills:

• 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, Continuous Integration and Continuous Deployment, 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 Software as a Service data platforms and customer data isolation.
• Experience integrating open lakehouse platforms with Snowflake.
• 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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.