{"id":2309634,"url":"https://alion.io/job/pearsonvue-data-engineer-iii","title":"Data Engineer III","company":{"id":94619,"name":"Pearson VUE","domain":"pearsonvue.com","url":"https://alion.io/company/pearsonvue","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":17,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":30000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":15},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Informatica","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Collibra","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-28T09:47:30Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-12T09:39:31Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"Data Engineer - Global Data Team\nRole Overview\nWe are looking for an experienced Data Engineer with 6-10 years of hands-on experience to join our Global Data team and help build reliable, scalable, and self-service data platforms that power enterprise-wide analytics and data products.\nIn this role, you will design, develop, and optimize modern cloud-based data platforms, lakehouse architectures, and distributed data pipelines. You will work extensively with technologies such as Google Cloud Platform (GCP), Google BigQuery, GCP Data engineering services, Data flow, Data Fusion, Data Streams, Cloud Storage, Cloud Composer/Airflow, dbt, Python, and SQL, while contributing to data governance, observability, automation, and AI-powered data engineering capabilities.\nThe ideal candidate is a hands-on engineer who enjoys solving complex data challenges, building reusable engineering frameworks, improving platform reliability, and enabling data teams through scalable self-service capabilities.\nKey Responsibilities\nDesign, develop, and maintain scalable ETL/ELT data pipelines supporting enterprise data products and analytics.\nBuild and optimize data solutions using Google BigQuery, GCS, Cloud Composer/Airflow, dbt, Python, and SQL.\nDevelop robust data ingestion and transformation pipelines from databases, SaaS applications, APIs, files, and other enterprise data sources.\nImplement and maintain API integrations and data ingestion frameworks for cloud and enterprise applications.\nDevelop reusable dbt models, transformation frameworks, and data quality processes.\nBuild and manage workflow orchestration using Apache Airflow / Google Cloud Composer.\nWork with CDC and data ingestion technologies such as Informatica CDC, Airflow, Composer, dbt, or similar platforms.\nDesign and implement modern data lakehouse architectures using BigQuery and related cloud technologies.\nOptimize data pipelines and BigQuery workloads for performance, scalability, reliability, and cost efficiency.\nImplement engineering best practices including CI/CD, version control, automated testing, deployment automation, and DevOps practices.\nContribute to data observability and monitoring frameworks, including pipeline health, data quality, SLA monitoring, and operational metrics.\nPartner with data architects, analysts, data scientists, product teams, and business stakeholders to deliver high-quality data solutions.\nContribute to data governance, metadata management, lineage, and data discovery capabilities.\nExplore and implement AI/ML and GenAI capabilities to improve data engineering workflows, automation, data discovery, and developer productivity.\nTroubleshoot complex data pipeline and platform issues and drive root-cause analysis and long-term improvements.\nHelp establish engineering standards, reusable frameworks, and best practices across the Global Data organization.\nChampion self-service data capabilities that improve the experience of data consumers and engineering teams.\nRequired Skills and Experience\n6-10 years of professional experience in Data Engineering, Data Platform Engineering, or a closely related field.\nStrong hands-on experience developing ETL/ELT pipelines and data transformation workflows.\nStrong programming experience with Python.\nStrong SQL skills, including experience with complex queries, optimization, and large-scale data processing.\nHands-on experience with dbt and modern data transformation practices.\nHands-on experience with Apache Airflow and/or Cloud Composer for workflow orchestration.\nStrong experience working with Google BigQuery or a comparable cloud data warehouse.\nExperience with Google Cloud Storage (GCS) and cloud-based data platforms.\nExperience building and integrating data pipelines using REST APIs and other data integration mechanisms.\nStrong understanding of data modeling, data warehousing, and modern lakehouse architectures.\nExperience working with large-scale distributed data pipelines and production data environments.\nExperience with Git, CI/CD, automated testing, and DevOps practices.\nStrong problem-solving and analytical skills with the ability to troubleshoot complex data engineering issues.\nAbility to work effectively in a global, collaborative, and cross-functional environment.\nExcellent written and verbal communication skills.\nPreferred Skills\nStrong experience with GCP data services, particularly BigQuery, GCS, Cloud Composer, and related services.\nExperience with Informatica CDC / Mass Ingestion or other change-data-capture technologies.\nExperience with additional cloud platforms such as AWS or Azure.\nExperience with data governance and metadata management platforms, such as Collibra or similar tools.\nExperience implementing data observability frameworks and tools.\nExperience with data quality, lineage, cataloging, and metadata management.\nExperience with Terraform or Infrastructure as Code.\nExperience with containerization and modern DevOps technologies.\nExposure to AI/ML and GenAI technologies, including using LLMs to automate or enhance data engineering workflows.\nExperience building self-service data platforms, reusable engineering frameworks, or data products.\nExperience with data security, privacy, access controls, and enterprise data governance.\nExperience optimizing cloud data platforms for performance and cost.\nWhat You Will Bring\nA hands-on engineering mindset with a passion for building production-grade data solutions.\nStrong ownership and accountability for the reliability and quality of data pipelines and platforms.\nA continuous-improvement mindset and enthusiasm for automation, standardization, and reusable frameworks.\nAbility to simplify complex technical problems and develop scalable solutions.\nCuriosity and willingness to learn and adopt emerging technologies, particularly AI/ML and GenAI.\nA strong focus on platform reliability, data quality, observability, and developer/user experience.\nAbility to collaborate effectively with globally distributed engineering, architecture, product, and business teams.\nStrong communication skills and the ability to explain complex technical concepts to both technical and non-technical audiences.\nPassion for building self-service capabilities that enable teams to discover, access, understand, and use data effectively.\nWhy Join Us\nBuild and scale next-generation cloud data platforms powering enterprise-wide analytics, data products, and AI initiatives.\nJoin Pearson, a global leader transforming lives through learning and innovation.\nWork hands-on with GenAI, AI-powered data engineering, and intelligent automation.\nShape the future of self-service data, data products, governance, and observability at scale.\nCollaborate with high-performing global data and technology teams solving real-world, high-impact problems.\nWork with modern technologies across GCP, BigQuery, dbt, Airflow/Composer, Python, and AI/ML.\nHave the opportunity to influence data engineering standards, architecture, and platform strategy.\nAccelerate your career in a fast-evolving, innovation-driven global data ecosystem.","description_format":"text","description_chars":7073,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Events & Ticketing","Sporting Events"],"lifecycle":[{"event":"open","at":"2026-10-12T00:33:25Z"}],"visa":[],"liveness":{"score":42,"band":"fade","label":"Fading","p_open":1,"p_active":0.562,"p_room":0.75,"age_days":13,"expected_fill_days":17,"reasons":["conf:3","stale_co","win:late","comp:brand"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/pearsonvue-data-engineer-iii","json_url":"https://alion.io/job/pearsonvue-data-engineer-iii.json","meta":{"generated_at":"2026-10-12T13:28:26Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":21053,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":94619},"rest":"https://alion.io/mcp/rest/get_company?id=94619"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpearsonvue-data-engineer-iii"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpearsonvue-data-engineer-iii"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpearsonvue-data-engineer-iii"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/pearsonvue-data-engineer-iii\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpearsonvue-data-engineer-iii"}]}