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Lucideus Technologies - Staff Data Engineer - ETL / Snowflake DB

Lucideus Technologies - Staff Data Engineer - ETL / Snowflake DB

LucideusBangalore
30+ days ago
Job description

What Youll Do :

  • Be the Data Tech Leader : Mentor engineers, champion data engineering best practices, and raise the bar for technical excellence across the org.
  • Architect at Scale : Design and lead petabyte-scale data ingestion, processing, and analytics platforms using Snowflake, Apache Spark, Iceberg, Parquet, and AWS-native services.
  • Own the Data Flow : Build streaming and batch pipelines handling billions of events daily, orchestrated through Apache Airflow for reliability and fault tolerance.
  • Set the Standards : Define frameworks for data modeling, schema evolution, partitioning strategies, and data quality / observability for analytics and AI workloads.
  • Code Like a Pro : Stay hands-on, writing high-performance data processing jobs in Python, SQL, and Scala, and conducting deep-dive reviews when it matters most.
  • Master the Lakehouse : Architect data lakes and warehouse solutions that balance cost, performance, and scalability, leveraging AWS S3 and Snowflake.
  • Solve Complex Problems : Elegantly and efficiently debug and optimize long-running jobs, data skew, and high-volume ETL bottlenecks.
  • Collaborate and influence : Work with the Product, AI / ML, and Platform teams to ensure that data solutions directly power real-time cyber risk analytics.
  • Innovate Constantly : Evaluate and introduce emerging data technologies (e.g., Flink, Druid, Rockset) to keep SAFE at the forefront of data engineering innovation.

What Were Looking For :

  • 8+ years of experience in data engineering, with a proven track record of designing and scaling distributed data systems.
  • Deep expertise in big data processing frameworks (Apache Spark, Flink) and workflow orchestration (Airflow).
  • Strong hands-on experience with data warehousing (Snowflake) and data lakehouse architectures (Iceberg, Parquet).
  • Proficiency in Python, SQL, Scala, Go / Nodejs with an ability to optimize large-scale ETL / ELT workloads.
  • Expertise in real-time data ingestion pipelines using Kafka or Kinesis, handling billions of events daily.
  • Experience operating in cloud-native environments (AWS) and leveraging services like S3, Lambda, ECS, Glue, and Athena.
  • Strong understanding of data modeling, schema design, indexing, and query optimization for analytical workloads.
  • Proven leadership in mentoring engineers, driving architectural decisions, and aligning data initiatives with product goals.
  • Experience in streaming architectures, CDC pipelines, and data observability frameworks.
  • Ability to navigate ambiguous problems, high-scale challenges, and lead teams toward innovative solutions.
  • Proficient in deploying containerized applications (Docker, Kubernetes, ECS).
  • Familiarity with using AI Coding assistants like Cursor, Claude Code, or GitHub Copilot.

    • Preferred Qualification :

  • Exposure to CI / CD pipelines, automated testing, and infrastructure-as-code for data workflows.
  • Familiarity with real-time analytics engines (Druid, Pinot, Rockset) or machine learning data pipelines.
  • Contributions to open-source data projects or thought leadership in the data engineering community.
  • Prior experience in cybersecurity, risk quantification, or other high-scale SaaS domain.

    • (ref : hirist.tech)

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