{"id":3357339,"url":"https://alion.io/job/calfus-data-engineer","title":"Data Engineer","company":{"id":3800027,"name":"Calfus","domain":"calfus.com","url":"https://alion.io/company/calfus","size_band":null,"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":"senior","employment_type":"full_time","work_mode":"on_site","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":null,"salary_estimate":{"min_usd":19500,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"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":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"AI Agents","optional":true},{"name":"Python","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-10-27T17:26:28Z","employer_posted_date":null,"last_verified_at":"2026-10-27T17:26:28Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"About Us:\nAt Calfus, we are known for delivering cutting-edge AI agents and products that transform businesses in ways previously unimaginable. We empower companies to harness the full potential of AI, unlocking opportunities they never imagined possible before the AI era. Our software engineering teams are highly valued by customers, whether start-ups or established enterprises, because we consistently deliver solutions that drive revenue growth. Our ERP solution teams have successfully implemented cloud solutions and developed tools that seamlessly integrate with ERP systems, reducing manual work so teams can focus on high-impact tasks.\nNone of this would be possible without talent like you! Our global teams thrive on collaboration, and we're actively looking for skilled professionals to strengthen our in-house expertise and help us deliver exceptional AI, software engineering, and solutions using enterprise applications.\nAs one of the fastest-growing companies in our industry, we take pride in fostering a culture of innovation where new ideas are always welcomed—without hesitation. We are driven and expect the same dedication from our team members. Our speed, agility, and dedication set us apart, and we perform best when surrounded by high-energy, driven individuals.\nTo continue our rapid growth and deliver an even greater impact, we invite you to apply for our open positions and become part of our journey!\nAbout the Role\nAs a Senior / Lead Data Engineer, you'll own the design and delivery of our cloud data platforms on AWS and Azure. You'll architect Lakehouse solutions built on Medallion Architecture, set the data modelling standards, and lead a team of data engineers delivering reliable, scalable pipelines. This is a hands-on leadership role: you'll make the architecture decisions and still be close enough to the code to write SQL and PySpark yourself. With 8–12 years of experience, you've designed data platforms, not just built pipelines on them.\nWhat You'll Do\nData Architecture & Platform Design\nDesign scalable data lake, lakehouse, and warehouse architectures on AWS and Azure that meet business requirements\nImplement Medallion Architecture (bronze, silver, gold) using Databricks and Delta Lake\nWork with stakeholders to gather requirements and translate them into technical specifications and architecture designs\nData Integration & Pipelines\nBuild and oversee ETL/ELT pipelines using Azure Data Factory, Airflow, SSIS, or equivalent tools\nUse Azure Databricks and PySpark for large-scale data processing\nOwn pipeline reliability — orchestration, monitoring, failure handling, and automation\nData Modelling\nDesign and maintain dimensional and relational data models (star, snowflake) for analytical workloads\nOwn schema design decisions and modelling standards across the platform\nDatabase Engineering & Performance\nWrite complex SQL queries, stored procedures, and transformations\nOptimise pipelines, queries, and Spark jobs for performance, scalability, reliability, and cost\nData Quality & Governance\nImplement data quality checks, validation, and governance best practices to ensure accurate and compliant data\nTeam Leadership\nLead, mentor, and guide data engineers, review code, and build a culture of continuous learning and improvement\nWhat You'll Need — Must Have\n6-12 years in data engineering, including experience leading data engineering teams\nStrong AWS or Azure experience (S3, Lambda, Glue / ADF, ADLS, Databricks) demonstrated through delivered projects\nMedallion Architecture — you've designed and implemented bronze/silver/gold layers on Databricks or Delta Lake\nData Architecture — you've designed end-to-end data platforms, not only built pipelines on them\nData Modelling — you've built dimensional and relational models, not only queried them\nAdvanced SQL — SQL Server, Postgres, Snowflake, or Redshift, including stored procedures and query tuning\nETL/ELT and orchestration tools such as SSIS, Azure Data Factory, or Airflow\nPython for data engineering — Pandas, NumPy, PySpark, scripting, and automation\nExperience with databases like Snowflake, Postgres, Redshift, and MongoDB\nFamiliarity with data formats like JSON, CSV, Parquet, and Pickle\nVersion control (Git), CI/CD, and code quality practices for data engineering projects\nBachelor's degree in Computer Science, Information Systems, Data Science, or a related field\nGood to Have\nHands-on experience across both AWS and Azure\nAzure SDK\nWorking with REST APIs and web scraping\nUnity Catalog or other data governance and cataloguing tools\nBenefits:\nAt Calfus, we value our employees and offer a strong benefits package. This includes medical, group, and parental insurance, coupled with gratuity and provident fund options. Further, we support employee wellness and provide birthday leave as a valued benefit.\nCalfus is an Equal Opportunity Employer.\nWe believe diversity drives innovation. We're committed to creating an inclusive workplace where everyone—regardless of background, identity, or experience—has the opportunity to thrive. 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