• Apply an in-depth understanding of data structures and information content. • Select, deploy, and manage the systems and infrastructure required for a data processing pipeline in support of the project requirements. • Investigate, create, and maintain data flows, data content, data element definitions with a goal of enterprise Master data integration. • Determine technical breath in data profiling from different sources and determine whether and how data can support business and data requirements of its intended use. • Develop and maintain common business definitions and metadata criteria for consistent metrics reporting across the enterprise. • Design the architecture for new data and analytics platform to support analytics and data science and machine learning. • Design the data models and data movement processes that support analytics and data science. • Recommend and implement patterns and best practices for data engineering. • Ensure quality processes are built into the design of the platform. • Understand the architectural difference between solution approaches and communicate the advantages/disadvantages of your recommendation to both technical and non-technical audiences. • Design and develop analytics and interactive visualizations that create business insights and clearly communicate data and trends. • Develop complex SQL queries to obtain data from our source systems. • Perform data validation and quality assurance to ensure data integrity and accuracy. • Collaborate with IT and business partners to identify data sources and align data domains to authoritative sources of data. • Enforce tactical enforcement of Data Governance policies and rules. • Research new technologies while keeping up-to-date with technological developments in relevant areas of Data Governance, Master Data, and Data Quality.

Role Description Turn 10 Studios is seeking a Data Engineer to join the Data Pipeline team and help design, build, and support modern data platforms that power studio‑wide decision making. This role focuses on developing scalable, high‑quality data pipelines and analytics systems using Azure‑based technologies. The Data Engineer will partner closely with business, design, test, and development teams to shape how data is captured, modeled, and consumed, enabling test‑driven methodologies and a culture of data‑driven development. - Design, build, and maintain scalable ETL and ELT pipelines supporting real‑time and batch analytics workloads. - Develop and optimize data models within lakehouse and warehouse architectures to support analytics and reporting needs. - Implement data processing solutions using Databricks, Azure Data Factory, Azure Synapse Analytics, and related services. - Ensure data quality, reliability, and performance across ingestion, transformation, and consumption layers. - Partner with cross‑functional stakeholders to define data requirements and improve how data is captured and used. - Create and maintain clear, concise technical documentation for data pipelines, models, and processes. - Establish documentation and knowledge‑sharing practices that improve discoverability and reuse across teams and studios. - Advocate for modern engineering practices and contribute to the evolution of the studio’s data architecture. Performance will be measured based on: - Quality, reliability, and scalability of delivered data solutions - Adherence to project timelines and delivery commitments - Effectiveness of documentation and knowledge sharing - Collaboration with stakeholders and contribution to data‑driven decision making Qualifications - Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical discipline, or equivalent professional experience. - Demonstrated expertise in SQL for analytics and data engineering use cases. - Proven experience designing and implementing scalable ETL processes, including data movement, orchestration, and quality controls. - Hands‑on experience with modern big data analytics platforms, including data lakes, distributed processing frameworks, and columnar storage formats. - Experience building and operating cloud‑hosted data systems, with strong preference for Microsoft Azure. Requirements - Azure Data Factory, Databricks, Azure Synapse Analytics - Spark‑based data processing - Data lake and lakehouse architectures - Parquet and Delta Lake formats - Azure Data Explorer and Kusto Query Language - Data modeling for analytics and reporting - Data quality, governance, and observability practices Benefits - Opportunity to work on the front edge of modern data engineering using Databricks, Azure Synapse Analytics, and Azure Data Explorer. - Direct impact on studio‑wide decision making, test‑driven development, and data‑driven culture. - Exposure to large‑scale lakehouse and warehouse analytics systems handling both real‑time and batch data. - Collaborative environment where data engineering directly influences business, design, testing, and development outcomes. Assessment Process Candidates will be evaluated through a combination of technical interviews, practical problem‑solving discussions, and assessment of prior experience building and supporting modern data platforms. Emphasis will be placed on applied data engineering skills, architectural judgment, and documentation practices.

PROJECT OVERVIEW Our client, a leading global provider of high-quality food products, including well-known brands and value-added premium products, is seeking a Data Engineer to support the development and evolution of a modern cloud data platform built on Snowflake. The role will focus on building scalable data pipelines, supporting platform migration from Dataiku to DBT, and enabling high-quality data for analytics and business intelligence. IN THIS ROLE, YOU WILL - Design and develop data pipelines and transformation workflows using DBT. - Build and optimize data models within Snowflake to support analytics and reporting. - Support the migration of orchestration and transformation processes from Dataiku to DBT. - Develop integrations between enterprise systems including CRM platforms and analytics environments. - Ensure data quality, consistency, and reliability across the data platform. - Implement and maintain data transformation best practices and coding standards. - Produce clear technical documentation for pipelines, models, and processes. - Collaborate with BI engineers, PM/BA, and Data Architects on platform design and improvements. - Proactively identify performance issues and optimize data pipelines. IF YOU ARE - 4+ years of experience in data engineering or data platform development. - Strong experience with Snowflake. - Hands-on experience with DBT for data transformations. - Advanced SQL skills and experience designing data models. - Experience building ETL/ELT pipelines in modern data platforms. - Familiarity with data integration patterns and enterprise system integrations. - Experience working in collaborative analytics engineering environments. - Ability to work with distributed teams with at least 4 hours overlap with US time zones. AS AN OPINOV8R, YOU WILL HAVE - Digital-First Approach: Great talent knows no borders! You can work from wherever you are — we hire and collaborate with professionals worldwide. - Remote Work Model: Balance your professional and personal life with our flexible working conditions, empowering you to deliver your best from anywhere. - Exciting Projects: Dive into impactful projects across industries that challenge and spark creativity. - Boost Your Expertise: Grow your career with continuous learning, development opportunities, and hands-on experience. - Join the Best Team Ever: Collaborate with our diverse and cross-cultural team of passionate technologists and creative thinkers. HOW’S THE HIRING PROCESS GOING We strive to make our hiring process smooth and transparent to find the perfect match for both sides. Steps may differ depending on the role, but here’s what to expect: - Initial Interview: If your background fits the role, we’ll invite you for an interview with a Talent Acquisition Specialist. - Technical Interview: Depending on the position, you may complete a technical assessment or test task. - Client Interview - Final Decision: After all steps, we’ll get back to you with the result and next steps.

Overview Location: Remote Employment Type: Full-Time Join Trissential and Help Shape a Cloud-Ready Future for Operational Technology Data If you’re a seasoned Data Architect who thrives at the intersection of industrial data, cloud architecture, and secure data movement—this is your opportunity. At Trissential, we partner with forward-thinking organizations that are modernizing how operational technology (OT) data is leveraged for analytics, automation, and AI. You'll join our client's team as the technical leader responsible for turning complex OT environments into governed, AI-ready cloud platforms built on Databricks. What’s in It for You? - High-impact architecture ownership across OT, cloud, and enterprise data domains - A role where your expertise shapes reference patterns, data governance, and long-term platform strategy - Opportunity to work across multiple senior stakeholder groups—Security, Networking, Operations, and Data Architecture - A collaborative project environment backed by Trissential’s culture of growth, transparency, and support - A chance to help an enterprise build an industrial-grade data fabric that scales for analytics and AI Your Role & Responsibilities - Partner with business and technology leaders to translate requirements into secure, scalable cloud architectures - Define target-state designs for safe and governed data movement from on-prem OT networks into Databricks - Evaluate and select approaches for ingesting/virtualizing historian data (especially OSI PI and AVEVA Connect) - Architect streaming, micro-batch, and batch data pipelines from edge to lakehouse - Design data layers (landing, curated, serving) aligned with Databricks lakehouse and Unity Catalog governance - Define AWS network and cloud security controls—VPC patterns, subnet designs, routing, encryption, private endpoints - Ensure Databricks E2 control plane and data plane security standards are followed, with compensating controls documented - Develop canonical time-series and asset-centric data models to support analytics and AI - Establish data quality SLAs, lineage standards, and AI data readiness frameworks - Produce ADRs, architecture blueprints, and engineering playbooks - Coach engineering teams and participate in architecture reviews - Collaborate with Security, Networking, and Compliance to validate controls and guide remediation - Measure and optimize cost, performance, and reliability across data pipelines and platforms Skills & Experience You Should Possess - Extensive background architecting data solutions within operational technology (OT) environments - Expertise designing solutions for industrial/asset-centric data domains - Deep experience with OSI PI, AVEVA, or similar historian platforms - Strong hands-on knowledge of Databricks, Spark, Delta Lake, and Unity Catalog - Proven mastery of data pipeline architecture—batch, micro-batch, streaming, CDC, and edge-to-cloud patterns - Advanced data modeling experience with time-series data and asset hierarchies - Strong AWS networking and security knowledge: VPCs, subnets, routing, IAM, KMS, private connectivity - Ability to interpret and implement enterprise Databricks security guidance (E2 architecture) - Excellent communication and negotiation skills with senior business and technical leaders - Familiarity with ML/AI platform requirements such as feature stores, lineage, and observability Bonus Points If You Have - Experience integrating AVEVA PI AF or AVEVA Data Views with Databricks - Prior contributions to enterprise data fabric or Databricks governance standards - Experience in regulated industrial or utility environments - Background working with safety, reliability, or compliance-heavy data ecosystems Education & Certifications You Need - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field - Cloud or Databricks certifications beneficial but not required What We Offer At Trissential, we care about delivering meaningful work experiences. When you join our client’s team through us, you receive industry-leading support and flexibility—without sacrificing benefits. - Competitive Compensation –$100–$110 per hour, depending on your skills, experience, and location. Final compensation is determined based on skill alignment, years of experience, and fair, market-based rates by geography. - Comprehensive Benefits for you and your dependents – Medical, dental, vision, free tele-health, HSA with company contribution, life and disability insurance, and 401k with matching - Paid Time Off –Offers paid time away from work - Remote-first engagement with a high-performing architecture and data engineering community - Opportunities for ongoing professional development and certifications - A people-first culture built on partnership, transparency, and growth Please note: This role is only open to individuals authorized to work in the United States. Ready to Shape the Future of Industrial Data? If you’re excited to architect secure, scalable, cloud-ready OT data platforms, we want to meet you. Apply today and take the next step in your architecture career with Trissential!