HYBRID ROLES - LOCAL CANDIDATES ONLY
Lead Data Engineer / Data Architect – Cloud, GCS, Data Lake (Banking – Irving, TX, Hybrid)
Remote Option Not Available
Duration: 12+ months contract with possibility of longer term extensions
Compensation: $70–$75/hr W2
Due to Client requirement, NO C2C, H1B, TN VISA, CPT OR OPT
Must be able to work directly on our W2 with no 3rd party involved!
If interested, please email your resume directly to [email protected]
No vendor resumes please!!
Play a critical leadership role in shaping the bank’s cloud data architecture, impacting analytics, compliance, and customer experience
Role:
Architect and implement enterprise-scale cloud data lakes to streamline and secure data for analytics and regulatory reporting
Design layered/lakehouse data models (e.g., Bronze/Silver/Gold), cloud bucket structures, retention/access policies, and scalable standards in alignment with financial industry governance
Lead data governance initiatives: support data lineage, documentation, compliance logs, and retention best practices in a regulated environment
Build and optimize secure ETL pipelines to ingest, organize, and curate raw and structured data for downstream use
Define naming conventions, access controls, and lifecycle management for Google Cloud Storage (or AWS S3/Azure Data Lake), with focus on privacy, security, and audit-readiness
Oversee data formats, file partitioning, compression, and backfill processes using Parquet, Avro, ORC, and similar standards
Collaborate cross-functionally with engineering, risk, business, and compliance teams to develop practical data solutions and ensure requirements are met
Document frameworks and mentor team members to ensure scalable, repeatable, and compliant data engineering practices
Required Qualifications
7+ years of professional data engineering experience, including 3+ years as a Lead Data Engineer or Data Architect (within banking/financial services preferred but not required)
Proven experience architecting data lake solutions on cloud platforms (preferably Google Cloud Storage, AWS S3, or Azure Data Lake)
Hands-on expertise with:
Layered data/lakehouse models (Bronze/Silver/Gold)
Bucket/storage structure design, naming conventions, lifecycle and retention policies, hierarchical access controls
File and storage formats such as Parquet, Avro, and ORC
Strong command of data partitioning, compression, backfills, and organization for large-scale regulated data environments
Experience designing curated data models for analytics, BI, regulatory, and executive reporting
Preferred/Bonus Skills
Financial industry or regulated data environment experience
Familiarity with Google BigQuery, Databricks, Snowflake, or similar analytics platforms
DevOps, CI/CD, or infrastructure automation in data engineering
Experience supporting data compliance (GDPR, CCPA, SOX, etc.) and secure data management initiatives
Leadership or mentoring of data engineering teams
Ready to help transform data in banking? Apply now and reach out directly for a confidential discussion!