{"id":2084234,"url":"https://alion.io/job/lifelancer-full-stack-data-engineer","title":"Full-Stack Data Engineer","company":{"id":3853997,"name":"Lifelancer","domain":"lifelancer.com","url":"https://alion.io/company/lifelancer","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["MX"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"Fivetran","optional":false},{"name":"Git","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Collibra","optional":true},{"name":"GitHub Actions","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true},{"name":"Terraform","optional":true},{"name":"Trino","optional":true}],"status":"live","first_seen_at":"2026-10-08T09:56:45Z","employer_posted_date":null,"last_verified_at":"2026-10-08T09:56:45Z","board_verified":false,"closed_at":null,"days_open":10,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":10},"description":"Job Title: Full-Stack Data Engineer\nJob Location: Zapopan, Jalisco, Mexico\nJob Location Type: Remote\nJob Contract Type: Full-time\nJob Seniority Level: We are looking for a passionate Full Stack Data Engineer who will help strengthen our data engineering capability with modern software engineering practices. This individual will build robust, maintainable, and scalable data solutions across the data lifecycle, while also contributing to the team’s wider engineering standards, tooling, and ways of working. \nThis is a hands-on engineering role for someone who is equally comfortable developing data pipelines, Python services, and automation for deployment and operations, and who can partner effectively with architects, analysts, product teams, and other engineers to deliver reliable data products. \nRoles & ResponsibilitiesDesign, build, and support scalable data pipelines, data products, and data applications that serve business and analytics needs. \n\nApply software engineering best practices to data engineering, including modular design, version control, code review, automated testing, documentation, and maintainable architecture. \n\nDevelop Python-based solutions for data processing, orchestration, integration, automation, and supporting application components where required. \n\nOwn and improve DevOps/DataOps practices for data solutions, including CI/CD, environment promotion, release automation, observability, incident response, and production support. \n\nDeliver robust, cost-effective, and automated solutions to address recurring business questions and analytical demands. \n\nDesign and implement data solutions aligned with enterprise standards, architecture roadmaps, and platform best practices, working closely with Data Architects and Solution Architects. \n\nTest and quality assure data and analytics solutions to ensure they are fit for release, including code assurance, unit testing, integration testing, data validation, performance tuning, and release management. \n\nSupport operational excellence through proactive monitoring, root-cause analysis, issue resolution, and continuous improvement of SLAs and service reliability. \n\nPromote engineering consistency across the team by disseminating best practices, coaching peers, contributing reusable patterns, and helping improve standards, tooling, and ways of working. \n\nEvaluate and adopt new technologies relevant to data engineering, software engineering, and platform automation, including proof-of-value assessments and contribution to business cases. \n\nContribute to estimates, delivery planning, and solution design for new data initiatives and enhancements. \n\nEnsure business data assets are delivered as trusted, discoverable, and reusable data products/services for broader enterprise consumption, in alignment with strategic data principles. \n\nCollaborate with stakeholders to translate business requirements into reliable technical solutions, define acceptance criteria, and establish appropriate operational and service expectations. \n\nMaintain ongoing professional development in modern data, cloud, and engineering practices to help keep AstraZeneca current with a changing technology landscape. \n\nMandatory SkillsStrong software engineering background, with hands-on experience building production-grade solutions using sound engineering principles such as modular design, testing, code review, and maintainability. \n\nStrong Python engineering skills, including building reusable packages, APIs, automation scripts, data processing components, and integration services. \n\nHands-on experience designing and operating solutions in Snowflake, including virtual warehouse configuration, resource monitors, governance, and performance tuning. \n\nExpert SQL for analytics and transformation, with strong skills in query optimization, pruning, caching behavior, and result set reuse. \n\nExperience building robust pipelines into Snowflake with tools such as dbt, Airflow, dataops.live, Fivetran, AWS Glue, or AWS Lambda, with strong understanding of staging patterns, incremental loads, CDC, retries, error handling, and observability. \n\nPractical experience with data modeling, including dimensional and normalized approaches, and strong understanding of schema design, standardization, clustering keys, micro-partitioning, and workload/performance strategies. \n\nExperience with dbt modeling layers, materializations, testing, project configuration, documentation standards, and data contracts. \n\nExperience implementing automated testing and quality controls for data solutions, including unit, integration, and data validation testing. \n\nStrong experience with CI/CD pipelines, Git-based workflows, and deployment automation for data and application components. \n\nExperience with DevOps/DataOps practices, including environment management, release management, infrastructure automation, monitoring, and production support. \n\nExperience integrating Python-based data engineering solutions with serverless and cloud-native services, such as AWS Lambda and AWS Glue. \n\nDemonstrated track record delivering solutions on modern data platforms such as Snowflake or Redshift, and integrating them with downstream analytics or visualization tools. \n\nStrong analytical and problem-solving skills, including diagnosing and resolving production issues in complex data environments. \n\nAbility to translate business requirements into reliable technical solutions and data products with clear ownership, SLAs, and acceptance criteria. \n\nStrong understanding of FAIR data principles and data product best practices, including discoverability, metadata, lineage, interoperability, access controls, versioning, and consumer-oriented design. \n\nEffective working independently and within cross-functional, cross-cultural teams, with the ability to communicate technical concepts clearly to non-technical stakeholders. \n\nDemonstrable passion for learning and for improving engineering practices across a team. \n\nDesired SkillsExperience using Starburst/Trino for distributed SQL across heterogeneous data sources. \n\nFamiliarity with Terraform, GitHub Actions, and highly automated platform or pipeline delivery patterns. \n\nExperience with infrastructure as code and environment provisioning in cloud-based data platforms. \n\nFamiliarity with metadata and catalog tooling such as Collibra to improve lineage, standards adoption, reuse, and observability. \n\nExperience using PySpark for large-scale data processing and transformation in distributed environments. \n\nExperience building lightweight application or service layers that complement data pipelines, such as APIs, internal tools, or operational utilities. \n\nExperience mentoring peers and helping establish engineering standards across a team or community of practice. \n\nSummaryThe Full Stack Data Engineer is responsible for the design, development, deployment, and operational support of scalable data products and data applications in a DevOps/DataOps delivery model. This role combines strong data engineering expertise with a solid software engineering background, especially in Python, cloud-native development, and engineering automation. \nThe role is expected not only to build reliable data solutions, but also to raise engineering maturity across the team by disseminating best practices in software design, testing, CI/CD, observability, reuse, and operational excellence. \nDate Posted\n27-Jul-2026Closing Date\n06-Aug-2026AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.\n\nThis job is curated by Lifelancer.Lifelancer is a talent-hiring platform in Life Sciences, Pharma and IT. The platform connects talent with opportunities in pharma, biotech, health sciences, healthtech and IT domains.\nPlease apply via Lifelancer platform to get connected to the application page and to find similar roles.\nOriginally posted on Himalayas","description_format":"text","description_chars":8437,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[{"name":"Mexico","iso":"MX","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Biotechnology","Internet Services","Freelance & Talent Marketplaces"],"lifecycle":[{"event":"open","at":"2026-10-08T11:28:15Z"}],"visa":[],"liveness":{"score":81,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.805,"p_room":1,"age_days":8,"expected_fill_days":27,"reasons":["seen:8","velocity","win:early","comp:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/lifelancer-full-stack-data-engineer","json_url":"https://alion.io/job/lifelancer-full-stack-data-engineer.json","meta":{"generated_at":"2026-10-18T13:33:46Z","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":20065,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-19T00:00:00Z"}},"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":3853997},"rest":"https://alion.io/mcp/rest/get_company?id=3853997"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Flifelancer-full-stack-data-engineer"},{"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%2Flifelancer-full-stack-data-engineer"},{"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%2Flifelancer-full-stack-data-engineer"},{"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/lifelancer-full-stack-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flifelancer-full-stack-data-engineer"}]}