XFORIA Inc
XFORIA Inc

Sr Data Engineer (Snowflake, MongoDB & AI Tools) - 100% Remote - W2 Contract

Remote • Posted 2 hours ago • Updated 2 hours ago
Contract W2
12 Months
No Travel Required
Remote
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Snowflake
  • MongoDB
  • AI
  • Gen AI
  • CoPilot
  • Cursor
  • GitHub
  • ETL/ELT
  • API
  • codex
  • claude
  • Devin
  • Jenkins
  • SonarQube
  • Python
  • SQL
  • SnowPipe
  • Snowpark
  • snowflake Cortex
  • snowPro

Summary

Job Details
Senior Data Engineer – Snowflake & MongoDB
Long Term Contract
100% Remote


Role Summary
We are looking for a Senior Data Engineer to design, build, and operate reliable data pipelines and platforms that turn AI Assistant, and DevOps data (Cursor, Codex, Claude, CoPilot, Devin and its usage, CI/CD Tools, code and Release quality, delivery impact metrics) into actionable intelligence. You will own Snowflake and MongoDB-based data solutions end to end: ingestion, transformation, modelling, monitoring, and production operations.

Key Responsibilities
  • Use generative AI coding assistants (such as GitHub Copilot or Cursor) as first-class tools for code scaffolding, optimization, complex transformations, and automated documentation. Validate and own all AI-generated outputs with rigorous testing.
  • Design and build scalable ELT/ETL pipelines ingesting data from APIs, databases, and event/log sources (e.g., Cursor, Codex, Claude, CoPilot, Devin, Jenkins, SonarQube, Git, Jira, AI-assistant telemetry) into Snowflake.
  • Hands-on experience using dbt to build and maintain data models, write tests, and generate documentation.
  • Hands On experience with data visualization libraries or tools such as PowerBI, Tableau
  • Implement automated data observability, quality checks, lineage tracking, and compliance frameworks to monitor data drift and maintain trusted data products.
  • Model data in Snowflake (staging, core, marts; dimensional/star schemas) and optimize performance and cost (clustering, warehouse sizing, query tuning, resource monitors).
  • Design and manage MongoDB collections, schemas, indexes, aggregation pipelines, and change streams; integrate MongoDB with the analytics layer.
  • Set up monitoring, alerting, and logging for pipelines and databases; lead incident triage, root cause analysis, and runbook creation.
  • Automate deployments with CI/CD, Git, and infrastructure-as-code; manage environments (Dev/QA/Prod) and release practices.
  • Implement RBAC, masking, encryption, and audit controls aligned with enterprise security and compliance.
  • Partner with analysts, BI developers, and product/delivery leads to translate business needs into data products and dashboards.

Required Skills
  • 5+ yrs hands-on: Snowflake: architecture, virtual warehouses, Snowpipe, Streams & Tasks, Time Travel, cloning, secure data sharing, semi-structured (VARIANT/JSON) handling, stored procedures, performance and cost optimization.
  • 3+ yrs hands-on: MongoDB: data modelling, indexing strategy, aggregation framework, replication/sharding concepts, backup/restore, performance tuning, Atlas or self-managed operations.
  • Languages: Advanced SQL and Python (pandas, requests, PySpark a plus); strong scripting (Bash).
  • Data integration: ETL/ELT design patterns, batch and incremental/CDC loads, idempotency, error handling and retries. Tools such as dbt, Airflow, Informatica, Talend, Fivetran, or equivalent.
  • Data concepts: Dimensional modeling, data warehousing, data lake/lakehouse concepts, data governance, metadata, and lineage.
  • Monitoring & operations: Pipeline observability, alerting (e.g., Grafana, Splunk, Datadog, CloudWatch), SLA/SLO management, incident and problem management, on-call/support participation.

Good to Have
  • Snowflake Snowpark or Cortex; SnowPro certification.
  • MongoDB or Snowflake certification (Associate/Professional DBA or Developer).
  • Familiarity with DevOps toolchain data (Jenkins, SonarQube, GitHub/GitLab, Jira) and DORA/engineering metrics and DevOps Practices
  • Exposure to AI/ML data preparation or AI-assistant usage analytics.
 
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91088983
  • Position Id: AT-199
  • Posted 2 hours ago
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