Role Description This is a role for an engineer who wants to own core components of a modern data platform. We are looking for a Staff Data Engineer to architect, build, and operate production data systems across Prodege. This is a deeply hands-on technical role. You lead by building production-grade systems, setting engineering standards, and delivering scalable data architecture, not by working strictly at an abstract planning level. If you prefer delegating execution or working solely on isolated pipelines, this is not the role for you. But if you are a technical lead who owns data platforms end to end, from ingestion, streaming, and Medallion modeling to observability, governance, feature store foundations, and deployment, keep reading. You will build and evolve platform capabilities for a business serving over 120 million registered users. Operating within a high-scale data environment featuring: - 400 Terabyte footprint - 100 Terabyte Iceberg lake - 50 million daily events - 500 million pipeline records You will deliver the data foundations that power analytics, experimentation, machine learning, and AI-driven decision making across all Prodege products. If you enjoy building distributed systems at scale, working closely with cross-functional technical teams, and driving an AI-first engineering strategy, this role is for you. What you will own - Architecture, implementation, and operational reliability of major data platform domains, including pipelines, modeling layers, and data services - High-scale batch, ELT, and near-real-time streaming pipelines powering business intelligence, machine learning, experimentation, and product analytics - Platform standards for data governance, schema evolution, data contracts, lineage, and end-to-end observability - Data infrastructure and feature pipelines supporting machine learning, experimentation frameworks, and AI-driven applications - Technical quality and engineering standards across the team through direct code contributions, architecture design reviews, and technical mentorship What makes this role exciting - You will directly shape core data platform capabilities that drive analytics, machine learning, and business intelligence across the enterprise - You will own major technical domains from initial system design through production deployment and lifecycle management - You will build data foundations across consumer rewards, performance marketing, customer experience, and multiple owned digital properties - You will operate at true engineering scale, managing a 400 Terabyte data footprint, 50 million daily events, 500 million daily pipeline records, 50 plus Kafka topics, and 300 thousand daily queries - You will establish platform patterns that accelerate Prodege transition to an AI-first software engineering model What you will do - Architect, build, and operate high-capacity batch, ELT, event-driven, and near-real-time streaming data pipelines - Construct production-grade data platform components utilizing Snowflake, dbt, Iceberg, Trino, Kafka, and modern lakehouse technologies - Design scalable data models adhering to Medallion architecture principles to support business intelligence, advanced analytics, and machine learning - Enforce platform discipline around data contracts, schema evolution, lineage tracking, access governance, and system observability - Optimize data infrastructure for performance, query speed, system reliability, availability, and cost efficiency - Partner cross-functionally with Engineering, Product, Analytics, Business Intelligence, and Machine Learning teams to deliver trusted data foundations - Apply AI-assisted engineering tools to accelerate development velocity, automated testing, system debugging, and technical documentation What you will bring - Five to eight or more years of hands-on data engineering experience building large-scale data systems, ideally in advertising technology, marketing technology, consumer internet, or high-volume marketplace environments - Advanced technical expertise with SQL, Python, Snowflake, and dbt - Demonstrated background designing, deploying, and operating production-grade batch, ELT, and streaming pipeline architectures - In-depth understanding of modern data architecture paradigms, including Medallion architecture, data contracts, schema evolution, event-driven systems, and data modeling - Practical experience building data systems that directly support analytics, experimentation platforms, and machine learning workloads - Proven ability to optimize data pipelines and storage systems for scale, reliability, throughput, and cost performance - Strong communication and technical leadership skills, with a track record of driving technical decisions through design reviews, code reviews, and cross-functional alignment Bonus points - Experience with Iceberg, Trino, Kafka, Flink, Kinesis, Spark, or related lakehouse and distributed streaming frameworks - Experience building ML feature pipelines, feature stores, or model training data infrastructure - Experience architecting self-service analytics frameworks or experimentation platforms - Experience with modern DataOps methodologies, workflow orchestration, and data observability tools - Experience leveraging modern AI-assisted software development tools to enhance engineering productivity Pay Transparency The anticipated base salary range for this position is $185,000 to $220,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Benefits - Comprehensive benefits package including medical, dental, vision, STD, LTD, and basic life insurance - Flexible PTO and paid sick leave prorated based on hire date - Eight paid holidays throughout the calendar year Equal Employment Opportunity Statement At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply. FCIHO Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

Role Description The Data Engineer is responsible for developing, implementing, and supporting scalable data pipelines and workflows across cloud platforms. This role focuses on designing, building, and optimizing ETL/ELT processes using Azure Data Factory, Azure Synapse, Snowflake, and related technologies, with an emphasis on automation, performance, and data quality. - Design and implement scalable data ingestion and transformation processes into Snowflake and downstream platforms - Migrate on-prem SQL Server data processes to Azure-based solutions to improve performance and scalability - Build and maintain ETL/ELT pipelines using Azure Data Factory and related tools - Develop, test, and optimize SQL scripts, stored procedures, and data pipelines to ensure data accuracy and efficiency - Implement monitoring, alerting, and self-healing capabilities to proactively resolve data pipeline issues - Partner with business stakeholders and cross-functional teams to deliver data integration and MDM solutions - Apply data standards, governance practices, and thorough documentation across all workflows - Support CI/CD processes to improve deployment, automation, and code quality - Mentor junior team members and contribute to continuous improvement of engineering practices - Participate in a Tier-3 on-call rotation to support production systems Qualifications - 2+ years of experience in data engineering, analytics, or a related field - Strong SQL expertise, including query optimization, complex joins, and stored procedures - Experience designing and building data pipelines in cloud environments (Azure Data Factory, Synapse, ADLS, etc.) - Hands-on experience with Snowflake (data loading, transformation, performance tuning) - Solid understanding of ETL/ELT processes and data warehousing concepts - Experience with version control (Git/TFS) and CI/CD practices - Strong attention to detail with the ability to manage multiple priorities - Effective communication and collaboration skills in a cross-functional environment Requirements - Exposure to Python for data processing, automation, or scripting - Experience with tools such as Databricks, Postgres, DBT, or similar - Familiarity with AI-enabled development tools (e.g., Claude Code, Cortex, Copilot) Benefits - Competitive pay - Medical, Dental and Vision Plans - Paid Holidays & PTO - Short and Long-Term Disability - Paid Life Insurance - 401(k) Retirement Plan - Employee Stock Purchase Plan - Lithia Learning Center - Vehicle Purchase Discounts - Wellness Programs

Role Description The Big Data Sr. Data Modeller role involves designing and implementing complex data models to support big data initiatives within an organization. The role requires expertise in data modeling, data architecture, and big data technologies. - Develop and implement data models for big data projects. - Collaborate with data scientists and engineers to optimize data models for performance and scalability. - Analyze and interpret complex data sets to derive insights and drive decision-making. - Define data modeling best practices and ensure adherence to data standards and guidelines. - Work closely with cross-functional teams to understand business requirements and translate them into data models. - Stay up-to-date with emerging trends in big data technologies and recommend innovative solutions for data modeling challenges. Responsibilities - Design, extend, and govern ontologies in OWL; develop schema, patterns, and modular models for reuse and scale. - Author SPARQL queries for data access, analytics enablement, and quality checks. - Define SHACL shapes for data validation; integrate validation into CI/CD and pipeline checkpoints. - Work with product owners and SMEs to convert competency questions and business requirements into semantic models and graph queries. - Curate and harmonize biomedical vocabularies (e.g., OBO Foundry, SIO, EBI) and align with enterprise data mappings. - Collaborate with data engineers to implement pipelines (e.g., Pandas, PySpark) for semantic enrichment, mapping, validation, and graph/warehouse loads. - Create and maintain semantic data dictionaries for mapping and transformation design and integrate with platforms such as Snowflake or Databricks when applicable. - Establish modeling guidelines, review processes, and versioning with Git. - Develop reference implementations, standards, and enablement artifacts for broader reusability. - Lead client workshops, solution design, and incremental delivery. - Mentor junior team members and contribute to proposals, POVs, and accelerators. Qualifications - Bachelors - Business Analytics - Bachelors - Computer Science - Bachelors - Statistics - Masters - Data Science Certifications - Certified Data Management Professional - Riversand - Cloudera Certified Developer for Apache Hadoop (CCDH) - Techieventures Technologies - Databricks Certified Associate Developer for Apache Spark 3.0 - Databricks Academy - IBM Certified Solution Developer - WebSphere IIS DataStage Enterprise Edition v7.5 - IBM - Oracle Database 12c Administrator Certified Associate - Oracle Required Skills - Aerospace Manufacturing - Agile Methodology - Automotive Manufacturing - Banking Capital Markets - Change Management - Client Relations - Cloud Computing - Collaboration Tools - Computer Vision - Consumer Electronics - Consumer Packaged Goods (CPG) - Data Engineering - Design Thinking - DevOps - Electronic Hardware - Entertainment Journalism - Executive Presence - Healthcare Payors - Inclusion - Industrial Manufacturing Processes - Insurance - Internet Businesses - Life Science - Machine Learning - {+ 15 more} Language - English (Required) - Language Proficiency - Proficient - C2 Job Type - Regular - Remote Type - Remote - Work Shift - Any (United States of America) Compensation The approximate annual base compensation range for this position is: 80,000 to 100,000 USD. “Los Angeles California-based candidates are not eligible for this role.” The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant’s experience, knowledge, skills, and abilities; geographic location; and internal equity. Benefits - Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter. - Make an impact – Help global enterprises solve business challenges that matter. - Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead. - Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day. - Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress. Company Description Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way.

Role Description We are seeking a Master Data Lead to drive the integrity, accuracy, consistency, and governance of critical business data across SAP and associated systems. This role plays a key part in ensuring high-quality master data that supports efficient operations, accurate financial reporting, effective procurement processes, and strong business decision-making. Working closely with teams across Procurement, Finance, Operations, and IT, you will act as the organization's subject matter expert for master data quality and governance. You will lead initiatives that strengthen data standards, improve processes, and enhance data reliability across the business. Key Responsibilities - Data Quality Management - Own and champion data quality standards across SAP and associated business systems. - Monitor, assess, and improve the accuracy, completeness, consistency, and integrity of master data. - Identify recurring data issues and implement sustainable solutions to prevent reoccurrence. - Conduct regular reviews and audits to ensure adherence to data standards and policies. - Establish and monitor data quality metrics, reporting on trends, risks, and improvement opportunities. - Investigate root causes of data-related issues and coordinate corrective actions with relevant stakeholders. - Master Data Governance - Maintain governance frameworks for key master data domains. - Define and document data standards, business rules, approval requirements, and maintenance procedures. - Ensure appropriate controls exist for the creation, modification, and retirement of master data. - Act as the custodian of master data policies and governance practices. - Facilitate data stewardship across business functions by defining roles, responsibilities, and accountability. - Procurement Data Management - Ensure the quality and integrity of vendor master data. - Oversee material categorization structures to support procurement and reporting requirements. - Maintain governance over pricing information and supplier price lists. - Identify and resolve data issues impacting purchasing, sourcing, inventory management, and supplier performance. - Finance Data Management - Support the accuracy and control of key financial master data, including: - General Ledger (G/L) accounts - Cost centers - Financial hierarchies - Approval workflows - Organizational and reporting structures - Partner with Finance to maintain data that supports reporting, budgeting, forecasting, and compliance activities. - Contribute to strong financial controls through effective master data management. - Continuous Improvement - Drive initiatives that improve data quality, reduce manual workarounds, and increase process efficiency. - Support ERP enhancements, system upgrades, and transformation projects from a data quality perspective. - Recommend process improvements and automation opportunities that enhance data integrity. - Promote a culture of accountability and ownership for data quality across the business. What Success Looks Like - Reduced recurring master data issues. - Improved master data quality across key business domains. - Reduced manual intervention resulting from poor data quality. - Increased reliability of operational and financial reporting. - Strong compliance with governance and approval requirements. - Greater stakeholder confidence in business data. Qualifications - Bachelor's degree in Finance, Accounting, Business Administration, Engineering or a related field. - Expertise in Data Quality Management and Master Data Governance. - Strong SAP knowledge. - Understanding of financial and procurement processes. - Experience in root cause analysis and process improvement. - Ability to influence stakeholders across multiple business functions. - Strong attention to detail and problem-solving skills. - Continuous improvement mindset with a focus on delivering sustainable outcomes. Benefits - An inspiring challenge to work with great co-workers on ambitious projects that change people's lives. - The chance to be a part of a global and fast-growing company. - An international work culture that encourages diversity, collaboration and inclusion. - Positive, flexible, and innovative work environment. - Support for personal growth and internal career development. - Company social events and milestone celebrations. - Internet at home for full-time employees.