Senior Data Architect at Welocalize

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Job Reference: #LI-JC1 Overview The Data Platform Architect is a senior individual contributor responsible for leading the design, implementation, and long-term stewardship of Welocalize’s enterprise data platform.   As part of a major initiative to modernize the organization’s data infrastructure, this role will drive the evolution of Welocalize’s analytics and data environment—transforming an established technology stack into a governed, scalable, and high-performance platform built on Redshift, dbt Core / dbt Cloud, Estuary, and Power BI.   Reporting directly to the Head of Data & Analytics individual will serve as both hands-on engineer and architectural lead, guiding the design, standards, and technical direction of the modernization initiative while collaborating closely with the Data Engineering Leader (execution) and the Director of Data Quality & Governance (oversight) to ensure the effort delivers a cohesive, sustainable platform that supports analytical growth and embeds governance and quality by design.   Once the transformation is complete, the Data Platform Architect will continue to guide the platform’s development, ensuring it evolves in a structured, business-aligned, and well-governed manner with strong data quality oversight. Main Duties: • Rapidly gain fluency with the current-state data infrastructure and absorb the design and assessment materials produced by prior consulting work, translating them into actionable technical and sequencing plans. • Proactively engage business stakeholders (Finance, Operational Leadership, FP&A) to understand high-priority business intelligence, reporting, and financial reconciliation needs. • Define, model, and translate complex business requirements into concrete data pipelines and robust transformation logic within dbt, ensuring data quality, consistency, and fitness-for-purpose for Power BI consumption. • Lead the architectural design and implementation of data modeling, transformation, and orchestration standards using dbt, Redshift, Estuary, and Power BI. • Partner with the Data Engineering Leader to plan and sequence modernization workstreams and ensure technical execution aligns with architectural standards. Additional India-based engineering resources will be positioned for deployment to this initiative. • Contribute directly to core dbt model and test development, ensuring speed, architectural quality, and maintainability. • Collaborate with the Director of Data Quality & Governance to embed data quality, lineage, and governance frameworks into the platform’s design—including the enablement of automated data quality testing, proactive monitoring, and standardized issue resolution workflows. • Explicitly design transformation logic to reconcile financial and operational data discrepancies and establish a Single Source of Truth for key metrics and metadata elements. • Drive the migration and modernization of legacy workflows (Matillion, Power BI DAX) into version-controlled, tested, and documented dbt models. • Establish and enforce best practices for Git-based workflows, CI/CD pipelines, and documentation across the data platform. Ensure the platform’s ongoing evolution remains structured, well-documented, and responsive to business analytical needs. • Own the framework and standards for platform documentation, ensuring models, transformations, and dependencies are consistently described, discoverable, and integrated with governance processes. Leverage automation and AI-assisted tooling (e.g., dbt auto-docs, lineage visualization, metadata capture) to streamline and scale documentation, lineage tracking, and quality reporting. • Mentor and upskill engineers and analysts supporting the initiative, embedding platform standards and reducing key-person risk. • Architect the semantic model to maximize discoverability, optimize performance, reduce Power BI Premium capacity strain, and enable self-service analytics for business users. • Develop and maintain metadata documentation that clearly defines dimensions and metrics in ways that are easy for other members of the data, operations, and business teams to understands. Required: • Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field strongly preferred; equivalent experience acceptable. Master’s degree or advanced certification in data science, data engineering or architecture is a plus. • 7–10 years of progressive experience in data engineering, data architecture, or related technical disciplines, including at least 3 years leading or designing cloud-based data platform implementations (e.g., Redshift, Snowflake, BigQuery). • Demonstrated success designing, implementing, and optimizing modern data stacks that include automated testing, documentation, and governance capabilities. • Deep expertise in data modeling and transformation using dbt (or equivalent frameworks). • Expert-level proficiency in SQL and data warehouse design principles. • Proven ability to translate abstract business requirements into scalable, production-ready data models and dbt transformation logic. • Strong proficiency in Python for automation, orchestration, and integration tasks related to data pipelines, testing, and CI/CD. • Experience with real-time and batch ingestion tools such as Estuary, Fivetran, or Airbyte. • Proficiency with Git-based development workflows, including branching, pull requests, and code reviews. • Hands-on experience implementing CI/CD pipelines for data or analytics environments. • Proven ability to lead complex technical initiatives and establish scalable engineering and documentation standards without formal managerial authority. • Experience mentoring engineers and promoting consistent development best practices. • Strong communication and collaboration skills, with the ability to engage both technical and business stakeholders. • Familiarity with AWS data ecosystem (S3, Redshift, Glue, IAM) or comparable cloud platforms. Preferred to have: • Significant experience working directly with financial or operational reporting teams to define P&L, margin, and utilization metrics. • Experience migrating legacy ETL or BI logic (e.g., Matillion, Power BI DAX) into code-based transformation frameworks such as dbt. • Familiarity with Matillion, including its orchestration, transformation, and scheduling patterns, to support transition planning and migration. • Experience with Power BI service administration, capacity management, and workspace governance. • Exposure to data quality, lineage, and metadata management frameworks and experience with automation or AI-assisted documentation tools.