• Lead the technical conversion of SAS datasets, programs, and logic to SQL Server • Analyze existing SAS workflows and translate them into efficient SQL Server–based solutions • Design, implement, and optimize SQL Server schemas, stored procedures, views, and queries • Own SQL Server administration, including: Performance tuning and indexing, Security and access controls, and b ackup, recovery, and reliability practices • Validate data accuracy and performance against existing SAS outputs • Collaborate with technical and business stakeholders to ensure a successful migration • Document architecture, migration patterns, and operational procedures

• Design and deploy scalable Google Cloud services in GCP. • Implement IAM access controls to ensure secure and compliant data environments. • Develop and implement robust data ingestion pipelines from diverse sources. • Develop and enforce data validation processes to maintain accuracy and reliability. • Enhance data quality and efficiency through continuous optimization. • Analyze raw data to uncover patterns, trends, and opportunities. • Produce clear design documentation and solution roadmaps. • Lead projects independently while collaborating effectively within larger teams. • Mentor and cross‑train junior and senior Data Engineers, sharing expertise on complex assignments. • Advance your skills through hands‑on experience and formal learning opportunities. • Support pre‑sales activities by providing accurate work estimates and technical input. • Partner closely with Project Management to deliver projects on time and within budget. • Travel occasionally as required for project or team needs.

• As a Senior Data Engineer at Orijin, you will be a technical leader responsible for building, scaling, and modernizing the company’s data platform. • Your primary focus will be on data modeling, pipelines, architecture, reliability, and performance, ensuring that data is trusted, timely, and production-ready. • As a member of the Enterprise Services team, you will partner closely with data analysts, engineers and product managers to shape how data is modeled and used. • You will bring an analytical mindset to pipeline design and enable high-quality insights across the organization. • You will ensure company-wide confidence in data quality and enable data-enabled differentiating products and services. • Design and evolve Orijin’s data architecture to support scalability, reliability, and near–real-time use cases. • Define standards for data modeling, orchestration, versioning, and deployment. • Own the design, build, and maintenance of production-grade data pipelines across batch and streaming workloads. • Architect and maintain data systems using tools such as AWS (S3, RDS, Redshift, Lambda, DMS, Glue etc.).

• Data modeling & transformation • Build and maintain DBT models in Snowflake — design layered architecture (staging, intermediate, marts), write data quality tests (Elementary) • Write clean, well-structured Python and SQL; participate in code reviews and help define engineering standards for the data team • Design and maintain data pipelines using Airflow (DAGs in Python) • Manage data integrations via Airbyte — starting with marketing sources (GA4, Facebook Ads, TikTok Ads) and expanding to other streams over time • Use AWS S3 as the primary storage layer — manage buckets, partitioning, and access control • Own CI/CD pipelines for data workflows — automated testing, deployment, and monitoring • Monitor data quality and pipeline reliability; proactively identify and fix issues before they reach downstream consumers • Work closely with analysts to understand their data needs and translate them into well-modeled datasets • Bridge the gap between raw data and analyst-ready tables — create models clearly so analysts can work independently