Senior Data Engineer

Highbrow LLC

United States

Remote

USD 140.000 - 190.000

Vollzeit

14 Tage+

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Zusammenfassung

Highbrow LLC seeks a Senior Data Engineer for a remote role supporting Kastle System. You will build and operate batch and streaming pipelines across SQL Server, cloud apps, device/event streams, and CRM systems, with strong Snowflake experience.

You will develop ingestion, transformation, and enrichment pipelines using Flink, Kafka, CDC, SQL, and Python/Java/Scala, and implement lakehouse layers with Iceberg and Trino.

Qualifikationen

  • 6+ years of hands-on experience in data engineering or data platform development.
  • Strong SQL and data warehousing capabilities.
  • Experience with Snowflake and lakehouse architectures.

Aufgaben

  • Build and operate production-grade batch and streaming data pipelines across SQL Server, cloud applications, device/event streams, CRM systems, and third-party sources.
  • Develop ingestion, transformation, and enrichment pipelines using Flink, Kafka, CDC, SQL, and Python/Java/Scala.
  • Implement lakehouse data layers using Iceberg and Trino.
  • Build dimensional and analytical models for buildings, tenants, credentials, devices, and people.
  • Implement CDC, late-arriving data, retries, backfills, schema evolution, and data reconciliation.
  • Integrate lakehouse with Snowflake, including Iceberg-backed tables, secure sharing, and data contracts.
  • Develop automated data-quality checks, pipeline monitoring, lineage, and dashboards.
  • Troubleshoot production data issues and optimize queries, storage, and compute.
  • Implement security controls and CI/CD pipelines, IaC, and environment promotions.
  • Participate in production support, incident resolution, and on-call duties.
  • Collaborate with Product, QA, DevOps, Analytics, and distributed teams.

Kenntnisse

SQL
Python/Java/Scala
Data modeling
Performance tuning
Data quality
CI/CD
Cloud data platforms

Ausbildung

Bachelor’s or Master’s Degree in CS/EE/Math

Tools

Apache Iceberg
Delta Lake
Apache Hudi
Trino
Spark SQL
Snowflake
Kafka
Flink
Debezium
Kubernetes
dbt

Jobbeschreibung

Senior Data Engineer (Client: Kastle System) [Remote. Strong Snowflake experience is a must-have; other details are provided below.]

Location: Remote

Note: Strong Snowflake experience is a must-have; other details are provided below.

Key Responsibilities:
  • 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.
  • 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.
Education:
  • Bachelor’s or Master’s Degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
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