{"id":3454462,"url":"https://alion.io/job/techbar-senior-data-engineer-databricks-aws","title":"Senior Data Engineer (Databricks / AWS)","company":{"id":4486116,"name":"Techbar","domain":"techbarsw.com","url":"https://alion.io/company/techbar-2","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":["Ukraine"],"countries":["UA"],"hiring_countries":["US","GB"],"hiring_countries_total":2,"salary":{"min":5000,"max":7000,"currency":"USD","period":"month","gross":false,"usd_annual":84000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Kinesis","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon CloudWatch","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS Glue","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Scala","optional":true}],"status":"live","first_seen_at":"2026-10-20T23:00:23Z","employer_posted_date":null,"last_verified_at":"2026-10-20T23:00:23Z","board_verified":false,"closed_at":null,"days_open":10,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":10},"description":"TechBar is a software services company working with clients across the US and Europe. We are investor-backed, growing steadily, and known for putting senior, thoughtful engineers in front of our clients.\n\nWe are looking for a Senior Data Engineer to join our client’s team at a wealth management firm modernizing its data platform using Databricks and AWS.\n\nAbout the Project\n\nYou will design, build, and maintain reliable data pipelines and lakehouse models that power analytics, reporting, and data products across the business.\n\nThe platform processes financial data, including client portfolios, transactions, positions, and performance. Some initiatives may involve migrating existing workloads from Snowflake to Databricks.\n\nResponsibilities\n\nBuild the lakehouse: Design and develop scalable batch and streaming pipelines on Databricks using Spark and Delta Lake, following a medallion architecture (Bronze / Silver / Gold).\n\nOwn data on AWS: Work with S3, IAM, and related AWS services to ingest, store, and secure data from internal systems and third-party financial data providers.\n\nModel for the business: Build clean, scalable, and well-documented data models for analytics, reporting, and downstream consumers.\n\nEnsure data quality and trust: Implement data quality checks, monitoring, and lineage. Manage access and governance using Unity Catalog.\n\nOptimize performance and cost: Tune Spark jobs, cluster configurations, and storage layouts to improve performance and control cloud costs.\n\nAutomate delivery: Apply CI/CD and infrastructure-as-code practices to Databricks workflows and environments.\n\nSupport migration: Assess and migrate data pipelines, models, and workloads from Snowflake to Databricks where needed.\n\nCollaborate: Work closely with analysts, data scientists, and business stakeholders to translate requirements into reliable data solutions.\n\nRequirements\n\n6+ years of experience in data engineering, including significant hands-on experience with Databricks in production.\n\nStrong knowledge of Apache Spark / PySpark and advanced SQL.\n\nSolid Python skills for data engineering.\n\nHands-on experience with AWS as the underlying cloud platform for data systems, including S3, IAM, and related data services.\n\nExperience with Delta Lake and lakehouse / medallion architecture.\n\nExperience building data models for analytics and reporting.\n\nExperience with CI/CD, Git, and production data operations, including monitoring, troubleshooting, and performance tuning.\n\nAbility to own data pipelines end-to-end, from design and implementation to production support.\n\nStrong understanding of data quality, security, governance, and cost optimization.\n\nExcellent communication skills, with the ability to collaborate with both technical and non-technical stakeholders.\n\nAbility to work independently and proactively in a distributed team.\n\nFluent English.\n\nCurrently based in the United States or the United Kingdom.\n\nTech Stack\n\nData Platform\n\nDatabricks\n\nApache Spark / PySpark\n\nDelta Lake\n\nUnity Catalog\n\nDatabricks Workflows\n\nDelta Live Tables\n\nCloud Infrastructure\n\nAWS S3\n\nIAM\n\nAWS Glue\n\nAWS Lambda\n\nKinesis / MSK\n\nCloudWatch\n\nLanguages\n\nPython\n\nSQL\n\nScala (a plus)\n\nEngineering Practices and Tools\n\nGit\n\nCI/CD\n\nTerraform or Databricks Asset Bundles\n\nData quality frameworks\n\nOrchestration with Databricks Workflows or Airflow\n\nAdjacent Technologies\n\nSnowflake (migration context)\n\ndbt\n\nBI tools used by downstream consumers\n\nNice to Have\n\nExperience migrating from Snowflake to Databricks or working on other large-scale data platform migrations.\n\nExperience with Unity Catalog governance and access management.\n\nExperience building streaming pipelines using Structured Streaming, Kafka, or Kinesis.\n\nExperience with Terraform or Databricks Asset Bundles.\n\nExperience with dbt.\n\nDatabricks certifications: Data Engineer Associate or Professional.\n\nExperience in wealth management, asset management, or broader financial services, particularly with portfolios, positions, transactions, market data, and reference data.\n\nExperience working with regulated or sensitive data, including PII, compliance, and audit requirements.\n\nWhat We Offer\n\n20 paid vacation days per year.\n\n10 paid sick days per year.\n\n6 additional special days off per year.\n\nCompany-provided equipment to ensure you have everything you need to work effectively.\n\nThe opportunity to contribute to a modern Databricks and AWS data platform in the financial services domain.\n\nA long-term opportunity within an international, distributed team.\n\nLocation\n\nWe are considering candidates based in the United States and the United Kingdom only.\n\nIf you are a Senior Data Engineer with strong Databricks, Spark / PySpark, Python, SQL, and AWS experience who enjoys taking ownership of data solutions end-to-end, we look forward to hearing from you!","description_format":"text","description_chars":4834,"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":[],"hiring_locations":[{"name":"United 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