Lead Data Engineer

Raleigh, NC, US • Posted 6 hours ago • Updated 6 hours ago

Contract W2

No Travel Required

On-site

$85/hr

Fitment

Dice Job Match Score™

⭐ Evaluating experience...

Job Details

Skills

Snow Flake Schema
SQL
Amazon Web Services
Python

Summary

Jersey Hired is scouting for a heavy-hitting Senior Data Engineer to join a global consulting powerhouse. This isn''t just about moving data from Point A to Point B, it’s about architecting a fortress.

We need a pro who can design, build, and operate secure, audited, and cost-efficient pipelines on Snowflake. You’ll be the master of the journey: taking raw ingestion through Data Vault 2.0 models and delivering it into high-impact consumption layers. If you’re a Terraform-wielding, dbt-loving, Airflow-orchestrating engineer who treats "audit-ready" as a lifestyle, we want to talk.

The Mission

Architect & Build: Design scalable ingestion frameworks using Qlik, Glue, and ETLs.
Model at Scale: Implement Raw → DV 2.0 (Hubs/Links/Sats) → Consumption patterns in dbt Cloud with obsessive testing (uniqueness, relationships, freshness).
Snowflake Mastery: Build performant objects (tables, streams, tasks) and fine-tune clustering and micro-partitioning for peak efficiency.
Orchestrate Excellence: Author Airflow (MWAA) DAGs and dbt Cloud jobs that are idempotent, rerunnable, and strictly tracked against SLAs.
Secure the Perimeter: Enforce RBAC/ABAC, masking, and row-access policies. You’ll operationalize controls that make auditors smile—think change management, separation of duties, and evidence capture.
Ops & Observability: Bake tests into dbt, monitor via ACCOUNT_USAGE, and forward metrics to Splunk/Datadog.
FinOps: Right-size warehouses and manage multi-cluster concurrency to keep performance high and costs low.

What You Bring to the Table

< data-path-to-node="8">The Basics

Bachelor’s Degree + 6 years of advanced data engineering/enterprise architecture experience.
OR a High School Diploma/GED + 10 years of the same high-level experience.

< data-path-to-node="10">Technical Must-Haves

Snowflake Power User: Deep experience in secure account setup, storage integrations, Snowpipe, and cross-region replication. You understand the networking "under the hood" (AWS PrivateLink, VPC/DNS flows).
dbt Cloud Specialist: You know Dimensional and Data Vault 2.0 modeling, Jinja/macros, and the discipline of a DEV/QA/UAT/PROD promotion flow.
Airflow (MWAA) Expert: You’ve built modular DAGs, handled backfills, and know exactly when to use Airflow vs. dbt’s native orchestration.
The Compliance Mindset: You’ve worked in regulated environments (SOX, GLBA, FFIEC, or PCI) and understand runbooks, PIR/RCAs, and audit log immutability.
Coding/Cloud: Advanced SQL, Python (ETL/Airflow), and AWS fundamentals (S3, IAM, CloudWatch).

Bonus Points (The "Cherry on Top")

Experience with Snowflake Governance (Universal Search, masking automation).
Familiarity with Iceberg/External Tables or Kafka-driven ingestion.
Observability tools like Great Expectations, Monte Carlo, or Collibra.
Platform Engineering: Reusable Terraform modules, FinOps charge-back utilities, and service-account hardening.
BI/Semantic Layer: Designing metric layers for ThoughtSpot, Looker, or Power BI.

Does your code survive an audit and your pipelines never miss an SLA? Apply now and let’s get to work.

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: 91173308
Position Id: 8903546
Posted 6 hours ago

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