{"id":992382,"url":"https://alion.io/job/veraxion-data-engineer","title":"Data Engineer","company":{"id":722518,"name":"Veraxion","domain":"veraxion.com","url":"https://alion.io/company/veraxion","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-17T04:24:19Z","employer_posted_date":null,"last_verified_at":"2026-09-17T04:24:19Z","board_verified":false,"closed_at":null,"days_open":46,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":46},"description":"We are seeking a Senior Data Engineer (Data Engineer III) who is passionate about building modern data platforms and solving complex engineering challenges at scale. In this role, you will own data products end-to-end, from understanding business problems and designing scalable architectures to building production-grade pipelines that support analytics, AI, and operational excellence.\nThe candidate will have responsibilities across the following functions:\nData Product Development:\nOwn data products from design through production.\nDesign, build, and maintain scalable data pipelines and data products using Databricks, Spark, Python, SQL, and AWS.\nDevelop robust batch and streaming pipelines aligned with modern Lakehouse architecture principles.\nBuild reusable ETL/ELT frameworks, curated datasets, and self-service data products for analytics, AI/ML, and operational reporting.\nOptimise pipelines for performance, scalability, reliability, and cost efficiency.\nImplement incremental processing, CDC, and metadata-driven engineering frameworks.\nSolution Design and Architecture:\nPartner with business stakeholders to understand requirements and translate them into scalable technical solutions.\nDesign end-to-end data architectures, reusable frameworks, and high-performance data models.\nEvaluate architectural trade-offs and influence technical direction across the data platform.\nDrive solution design from concept through production deployment.\nEngineering Excellence:\nBuild production-grade solutions with a strong focus on quality, testing, observability, security, and reliability.\nImplement automated data validation, monitoring, lineage, and operational best practices.\nWrite clean, maintainable code and contribute to reusable frameworks, CI/CD, DataOps practices, and code reviews.\nTroubleshoot production issues and continuously improve platform performance and developer experience.\nBusiness Partnership:\nCollaborate with business stakeholders, product owners, analysts, architects, and engineers to solve high-impact business problems.\nTranslate business requirements into scalable data products and trusted datasets.\nCommunicate technical concepts effectively to both technical and non-technical audiences.\nTake end-to-end ownership of solutions from discovery and design to production support.\nRequirements:\n10+ years of experience in Data Engineering, with experience delivering enterprise-scale data platforms.\nStrong expertise in Databricks, Apache Spark (PySpark), Python, and SQL.\nHands-on experience building cloud-native data platforms on AWS.\nStrong understanding of distributed data processing, Lakehouse architecture, ETL/ELT, and modern data engineering practices.\nExperience designing scalable data models and optimising large-scale data pipelines.\nStrong software engineering fundamentals, including Git, CI/CD, testing, and code quality.\nExcellent communication skills with the ability to influence stakeholders and lead technical 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