Technical Lead - Snowflake Data Warehouse & Migration
$76.73k - $127.88kHighbrow Llc
Job Description Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Talent Model. Project Talent Model (PTM) is a talent model that is tailored specifically for long-term, onsite client service delivery. Recruiting for this role ends on Sep 30th, 2026. Work you'll do/Responsibilities As part of the Data & Analytics Foundry you will support numerous business product teams in designing, building, and operating modern data products and platforms across a scale delivery program (onshore/offshore). Your focus will be on delivering reliable, performant, and cost-effective data pipelines and curated datasets to enable analytics and downstream applications.
- Design, build, and support scalable batch and near-real-time data pipelines on AWS.
- Design robust ingestion patterns from source systems into S3 and into Snowflake.
- Develop transformation layers and curated datasets in Snowflake, including dimensional/data product modeling for analytics and downstream applications.
- Implement orchestration and workflow automation on AWS with retries, backfills, and idempotency.
- Build reusable Python components for ingestion, validation, and transformations; apply standards through code reviews and testing.
- Support Snowflake performance and cost optimization through warehouse sizing, concurrency patterns, query tuning, clustering/micro-partition considerations, and workload isolation.
- Partner with stakeholders to translate requirements into well-defined datasets and data contracts.
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
- Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
- 4+ years of experience as a Data Engineer delivering production-grade data pipelines and curated datasets.
- 4+ years of hands‑on experience with SQL and Python, including Snowflake and/or PySpark for scalable data processing and ELT.
- 4+ years of experience designing, building, and supporting batch and near-real-time data pipelines on cloud platforms (AWS preferred; Azure/GCP acceptable).
- Experience with data integration frameworks and orchestration tools.
- Working knowledge of Lakehouse/warehouse architectures and ELT patterns.
- Knowledge of DevOps principles: CI/CD pipelines, version control, Infrastructure-as-Code.
- Ability to optimize data storage, partitioning, file formats (Delta, Parquet), and performance.
- Understanding of data quality, data governance, and metadata management.
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
- Limited immigration sponsorship may be available.
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.
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