{"id":3168345,"url":"https://alion.io/job/syncron-senior-data-engineer","title":"Senior Data Engineer","company":{"id":2761282,"name":"Syncron","domain":"syncron.com","url":"https://alion.io/company/syncron-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":62000,"max_usd":102000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":108},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Hudi","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"IAM","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"OpenSearch","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"dbt","optional":true},{"name":"Kubeflow","optional":true},{"name":"MLFlow","optional":true},{"name":"Scikit-learn","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2026-10-23T10:27:52Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-25T10:40:01Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"EazyStock is a “startup” within Syncron, a global market leading company developing solutions for after market service optimization. Whilst Syncron’s client base is made of up of large enterprises (e.g. Manitowoc, Mazda, DTNA and JCB), EazyStock work with small to medium sized companies, helping them to optimize their inventories and achieve high levels of customer satisfaction without having excess capital tied up in redundant inventory.\nWe at EazyStock are an entrepreneurial and international team operating in Europe, Asia and the USA, developing and selling the best cloud-based inventory optimization software solution on the market. Nevertheless, we know that we can only help SMB’s if they know about EazyStock, and how this best-in-class solution will improve their customer satisfaction, increase their profits and reduce their inventory investment!\nAbout the role\nWe are looking for a Senior Data & AI Engineer to establish the data foundation of EazyStock - an engineer who owns the whole path from raw operational data to a model or an ML&LLM-powered feature in production.\nToday our product data lives in operational databases and is consumed directly by analytics and early AI/ML use cases. Your mission is to change that: to design and build a lakehouse on Apache Iceberg, AWS Glue and Amazon Athena that provides a governed, read-only replica of product data, dramatically better analytics capabilities, and high-quality, contract-backed data feeds into Qlik and our AI/ML and GenAI workloads.\nWhat would you do?\nLakehouse & Data Platform\nDesign and build the EazyStock lakehouse on S3 with Apache Iceberg as the table format, AWS Glue for ETL/ELT and cataloging, and Amazon Athena as the query engine.\n\nBuild reliable data integration and ingestion from operational sources.\n\nDeliver a governed analytical replica that removes reporting load from production systems.\n\nDesign partitioning, compaction, snapshot and retention strategies; own query performance and cloud cost efficiency.\n\nData Modelling, Contracts & Governance\nDeliver clean, well-modelled data into Qlik Cloud and into AI/ML consumers.\n\nDefine and operate data quality and data governance standards, with automated validation and meaningful alerting.\n\nIntroduce data contracts, schema evolution discipline and DataOps practices so producers and consumers can evolve independently.\n\nEstablish metadata management, data catalogs and lineage as a first-class part of the platform.\n\nDataOps & Automation\nBuild CI/CD for data pipelines, infrastructure and configuration using GitHub, Jenkins and AWS DevOps tooling; treat infrastructure as code.\n\nImplement observability for pipelines: metrics, logging, failure modes, SLAs and runbooks.\n\nDesign for repeatability and rollback - no manual production surgery.\n\nAI/ML & MLOps\nBuild and operate MLOps pipelines on AWS - model packaging, deployment, versioning, monitoring and retraining.\n\nSupport our GenAI initiatives: data curation and indexing for RAG, embedding pipelines, and Amazon OpenSearch as a vector store, with models served through Amazon Bedrock.\n\nBring engineering discipline to AI work - evaluation, observability, cost control and security - so that AI features are supportable, not experiments in disguise.\n\nWho you are? / What we expect:\n6+ years of professional experience spanning data engineering and software engineering, with production systems you owned end to end and still stand behind.\n\nStrong experience designing ETL/ELT pipelines, data models, and data integrations across heterogeneous sources.\n\nStrong data modelling skills, and real experience with metadata management, data catalogs and lineage.\n\nPractical experience with data quality and data governance.\n\nExperience with data contracts, DataOps practices and schema evolution in a multi-consumer environment.\n\nConfident with DevOps and CI/CD: Jenkins or equivalent, infrastructure as code, containerization (Kubernetes).\n\nDeep, practical experience with the AWS data stack - S3, AWS Glue, Amazon Athena, IAM, Lambda - and with the operational side of running workloads in the cloud.\n\nHands-on experience with Apache Spark, Apache Iceberg (or a comparable open table format such as Delta Lake / Hudi) - including the operational realities: compaction, partition evolution, snapshot management.\n\nStrong SQL and strong PostgreSQL - query optimization, indexing, execution plans, replication and CDC.\n\nStrong Python and solid production Java - you can own a backend service, not just call one.\n\nExperience integrating with Qlik or another enterprise BI platform.\n\nData Engineering Certificate: Google Professional Data Engineer, Microsoft Certified Fabric Data Engineer, AWS Certified Data Engineer, Databricks Certified Data Engineer, Snowflake SnowPro Advanced Data Engineer, or equivalent.\n\nProven ability to mentor and upskill engineers who are strong developers but new to data.\n\nThe icing on the cake:\nClassical ML familiarity - scikit-learn, XGBoost, pandas.\n\nA track record of leading a greenfield data platform build or a significant cloud data migration.\n\nExperience with Airflow, dbt or similar.\n\nExperience with SageMaker, MLflow, Kubeflow or comparable model lifecycle tooling.\n\nWorking experience with LLM-based systems - RAG, embeddings, vector databases, or LLM APIs in a production or serious prototype context\n\nPractical experience with MLOps: deploying models to production, versioning, monitoring and retraining - and a willingness to own the model lifecycle, not just the data that feeds it.\n\nDomain experience in Supply Chain, Inventory, Pricing or Service Fullfilment.\n\nWe offer:\nImpactful Work - Your contributions will directly shape the future of EazyStock’s product and deliver measurable value to customers worldwide.\n\nInnovation-Driven Culture - Join a team that thrives on creativity, collaboration, and cutting-edge technology.\n\nProfessional Growth - Opportunities to lead strategic initiatives, influence product direction, and expand your expertise in AI and SaaS.\n\nGlobal Environment - Work with colleagues and customers across multiple countries in a truly international setting.\n\nFlexibility - A hybrid work model that supports work-life balance.\n\nUnsure if you meet all the job requirements but passionate about the role? Apply anyway! Syncron values diversity and welcomes all Candidates, even those with non-traditional backgrounds. We believe in transferable skills and a shared passion for success!","description_format":"text","description_chars":6452,"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":["Hybrid work"],"hiring_locations":[{"name":"Poland","iso":"PL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Field Service Management Software","Supply Chain & Logistics Software"],"lifecycle":[{"event":"open","at":"2026-10-23T17:58:40Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":51,"reasons":["seen:1","velocity","win:early"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/syncron-senior-data-engineer","json_url":"https://alion.io/job/syncron-senior-data-engineer.json","meta":{"generated_at":"2026-10-25T22:21:45Z","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":31585,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"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":2761282},"rest":"https://alion.io/mcp/rest/get_company?id=2761282"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsyncron-senior-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%2Fsyncron-senior-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%2Fsyncron-senior-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/syncron-senior-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsyncron-senior-data-engineer"}]}