{"id":2702297,"url":"https://alion.io/job/youriteams-data-engineer-pyspark","title":"Data Engineer (PySpark)","company":{"id":4441827,"name":"YourITeams","domain":"youriteams.com","url":"https://alion.io/company/youriteams","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Traffit","truth_index":{"grade":"B","score":75,"open_postings":14,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_company_offices","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["PL"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":57000,"max_usd":146000,"period":"year","method":"global_role_seniority_cell","sample_n":578},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-08-27T12:25:06Z","employer_posted_date":"2026-08-27","last_verified_at":"2026-10-18T00:09:34Z","board_verified":true,"closed_at":null,"days_open":51,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":51},"description":"Job Overview\nWe are seeking a Regular Data Engineer (PySpark) to join a team working with production ETL pipelines on AWS. The person in this role will apply strong PySpark skills within an existing architecture, independently deliver tasks, and diagnose common production issues. This position focuses on practical implementation and operational excellence rather than end-to-end architecture design.\nResponsibilities\nImplement data transformations and ETL logic using PySpark.\nMaintain and develop existing AWS Glue jobs and related pipelines.\nInvestigate and resolve pipeline failures using logs, error messages, and basic metrics.\nDiagnose and mitigate Spark performance issues (partitioning, shuffle, skew, joins).\nChoose appropriate partitioning and join strategies for given workloads.\nHandle error scenarios in ETL processes, including retries, reprocessing, and partial failures to avoid duplicate processing.\nWork with large volumes of data and many files without creating uncontrolled parallelism.\nFollow established architectural patterns and implement solutions that integrate with the current system design.\nSupport data migration or batch processing tasks as needed.\nQualifications\n2-4 years of experience as a Data Engineer or in a similar role.\nPractical, hands-on experience with PySpark / Apache Spark.\nSolid understanding of key Spark concepts, including partitioning, shuffle, repartition vs coalesce, broadcast joins, and data skew impact.\nPractical experience with AWS services, especially AWS Glue, Amazon S3, and Amazon CloudWatch.\nExperience building, maintaining, or enhancing ETL/data processing pipelines.\nAbility to diagnose common Glue and PySpark issues from logs and basic metrics.\nExperience handling ETL error scenarios: retries, reprocessing, partial failures, and preventing duplicate processing.\nBasic understanding of idempotency and safe restart strategies after failures.\nExperience processing large data volumes or many files and familiarity with batch migration processes.\nStrong SQL skills and familiarity with joins, aggregations, filtering, grouping, and ranking.\nBenefits\nRemote working.\nUnique TEAL culture, relationship- and respect-driven community, non-corporate atmosphere.\nAgile approach and no bureaucracy.\nOutstanding integration trips to various places in Europe.\nActivities to support your well-being and health.\nLuxmed Gold Extended medical care and Multisport Plus benefit.","description_format":"text","description_chars":2432,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Poland","iso":"PL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-16T11:30:26Z"}],"visa":[],"liveness":{"score":13,"band":"cold","label":"Long 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