{"id":3010508,"url":"https://alion.io/job/rearc-lead-data-engineer-2","title":"Lead Data Engineer","company":{"id":6420,"name":"Rearc","domain":"rearc.io","url":"https://alion.io/company/rearc","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":4000000,"max":6500000,"currency":"INR","period":"year","gross":null,"usd_annual":68679},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-10-21T14:38:35Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-24T00:50:27Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"At Rearc, we're committed to empowering engineers to build awesome products and experiences. Success as a business hinges on our people's ability to think freely, challenge the status quo, and speak up about alternative problem-solving approaches. If you're driven by the desire to solve problems and make a difference, you're in the right place!\nOur approach is simple: empower our people with the best tools possible to make an impact within their industry. We're on the lookout for people who thrive on ownership and freedom, possessing not just technical depth but also executive presence and business judgment.\nFounded in 2016, we pride ourselves on fostering an environment where creativity flourishes, bureaucracy is minimal, and individuals are encouraged to challenge the status quo. We're not just a company; we're a community of problem-solvers dedicated to improving the lives of fellow software engineers and the customers we serve.\nLead Data Engineer - Rearc\nWhat You Bring\n8+ years of hands-on experience in data engineering, designing and delivering production-grade data platforms.\n\nExpert-level knowledge of Apache Spark, including deep understanding of runtime internals, performance tuning, and optimization to build scalable, high-performance pipelines.\n\nProficient in writing clean, production-quality code in Python; hands-on Scala experience is a strong plus for advanced Spark and performance-critical workflows.\n\nProven experience building and productionalizing data solutions on Databricks, including Delta Lake architectures, Unity Catalog governance, and Databricks Workflows. Databricks certification is a strong advantage.\n\nHands-on expertise with at least two major cloud platforms (AWS, Azure, GCP) and in-depth experience with at least one, utilizing cloud-native services such as AWS Redshift, Glue, S3; Azure Synapse, Data Factory, ADLS; or Google BigQuery, Dataflow, GCS.\n\nEnd-to-end leadership of data engineering projects in client-facing or consulting environments, managing technical scope, stakeholder engagement, and timely delivery without compromising quality.\n\nStrong DataOps practice: CI/CD for data pipelines, automated testing, observability, and infrastructure-as-code are integral to your workflows.\n\nBroad experience in ETL/ELT design, data warehousing, lakehouse architectures, and data modeling, with the ability to select and apply the right approach for diverse scenarios.\n\nExcellent communicator, able to engage effectively with both technical and non-technical stakeholders, from C-level executives to junior engineers.\n\nWhat You'll Do\nAs a Lead Data Engineer at Rearc, you’ll be the technical lead for complex, client-facing data engineering projects. You’ll own both architecture and implementation.\nLead Client Data Engagements: Serve as the senior technical lead on client projects, owning the architecture, guiding the build, managing delivery risk, and ensuring the shipped solution aligns with client promises.\n\nBuild and Productionize Data Solutions: Design, implement, and optimize scalable, reliable data pipelines and lakehouse architectures on Databricks and cloud platforms. Set the engineering standards for delivery through active coding and review.\n\nArchitect for Scale and Reliability: Translate complex client requirements into robust technical solutions, reference architectures, and data models built for durability and maintainability.\n\nDrive Technical Delivery: Oversee technical scope and timelines, proactively surface blockers, and coordinate with project managers and stakeholders to keep engagements on track.\n\nMentor Data Engineers: Coach junior and mid-level engineers through paired programming, code reviews, and constructive feedback.\n\nPromote Knowledge Sharing: Develop and contribute technical blogs, reference architectures, and internal guides based on practical client experiences.\n\nChampion DataOps Practices: Establish and uphold modern engineering standards, including automated testing, pipeline observability, version control, CI/CD, and comprehensive documentation.\n\nIf you’re passionate about data engineering, committed to engineering excellence, and energized by solving challenging problems for clients, Rearc offers a high-impact role with significant opportunity for growth and leadership.\nRearc is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. 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