Data Engineer II

Work You'll Do/Responsibilities

• Support numerous business product teams in designing, building, and operating modern data products and platforms across a scale delivery program (onshore/offshore).
• Deliver 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.
• 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.

Required Qualifications

• 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.
• Able 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.

Preferred

• Agile delivery experience.
• Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
• Can operate independently or with minimum supervision.
• Excellent written and communication skills.
• Ability to deliver technical demonstrations.