Senior Data Engineer

Senior Data Engineer

Client: Kastle System

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.