{"id":3560440,"url":"https://alion.io/job/mastek-data-engineer","title":"Data Engineer","company":{"id":59435,"name":"Mastek","domain":"mastek.com","url":"https://alion.io/company/mastek","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":113000,"max_usd":214000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1343},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"GCP","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2026-10-29T00:00:00Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-02T12:15:40Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Job Title\nData Engineer (DBT, Snowflake, Python)\nExpected Work Experience\n8-10 Years\nJob Location\nUSA\nJob Summary\nWe are looking for a skilled Data Engineer with strong hands-on experience in building scalable and efficient data pipelines. The ideal candidate will have deep expertise in DBT, Snowflake, and Python, and a solid understanding of modern data engineering practices. Candidate must have relevant experience of 8-10 Years. You will be responsible for designing, developing, and optimizing data pipelines and transformation workflows to support analytics, reporting, and business intelligence needs.\nKey Responsibilities\nDesign, develop, and maintain scalable data pipelines using DBT, Snowflake, and Python.\nBuild and manage data transformation workflows using DBT (models, macros, testing, and documentation).\nDevelop efficient data ingestion and processing pipelines using Python.\nOptimize Snowflake data models, queries, and performance for large-scale datasets.\nEnsure data quality, reliability, and consistency through testing and validation frameworks.\nCollaborate with data analysts, business teams, and stakeholders to understand data requirements.\nImplement best practices for data modeling, version control, and pipeline orchestration.\nMonitor and troubleshoot data pipeline issues and performance bottlenecks.\nMaintain clear and structured documentation for data workflows and pipelines.\nDeliver robust and scalable data pipelines that support analytics and reporting needs.\nDevelop and maintain DBT-based transformation frameworks to standardize data transformations.\nProduce optimized Snowflake data models and queries for high-performance analytics.\nEnsure delivery of high-quality, reliable datasets for analytics and reporting.\nOther Capabilities\nAbility to work effectively as a contractor in a cross-functional environment with data analysts, engineers, and business stakeholders.\nStrong problem-solving and analytical mindset with attention to detail and data quality.\nCapability to work on enterprise-scale data platforms and support complex data ecosystems.\nAdaptability to evolving data engineering tools, frameworks, and best practices.\nGood communication skills to explain technical concepts to non-technical stakeholders.\nQualifications and Skills\n8-10 years of hands-on experience in Data Engineering, with a focus on building scalable data pipelines.\nStrong expertise in DBT (Data Build Tool), including models, macros, testing, and documentation.\nSolid experience with Snowflake, including data warehousing, performance tuning, and optimization.\nStrong expertise in Python for data processing and pipeline development.\nGood understanding of SQL and data modeling concepts (star schema, dimensional modeling).\nExperience with data pipeline orchestration tools (such as Airflow or similar).\nFamiliarity with data quality and testing frameworks to ensure reliable datasets.\nStrong problem-solving and analytical skills for diagnosing and resolving data issues.\nExperience working in cloud environments (AWS, Azure, or GCP).\nFamiliarity with CI/CD practices for data pipelines and automated deployments.\nExposure to real-time or streaming data pipelines is a plus.\nExperience in enterprise-scale data platforms and large-scale data environments.\nBackground or familiarity with Data Automation & AI, Data Engineering, Data Analytics, and Databricks or similar 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