{"id":1445012,"url":"https://alion.io/job/careator-technologies-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3800664,"name":"Careator Technologies","domain":"careator.com","url":"https://alion.io/company/careator-technologies","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":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":22000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Databricks","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-29T04:09:37Z","employer_posted_date":null,"last_verified_at":"2026-09-29T04:09:37Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"Role : Senior Data Engineer (6 - 8+ Years)\n\nLocation : Bengaluru (Electronic City, Phase 1)\n\nExperience : 6 - 8+ Years\n\nInterview : Will also be Face to Face.\n\nMode of work : WFO (Work from office, 5 days) - no hybrid here.\n\nRole Overview : \n\nWe are looking for a highly skilled Senior Data Engineer to support the DKSH Analytics program. The candidate will be responsible for designing, building, and optimizing scalable data pipelines on Azure, supporting sales, inventory, and business analytics use cases. The role requires strong expertise in Azure data services, Python/PySpark, SQL, and a solid understanding of sales and inventory domain processes.\n\nPrimary Responsibilities : \n\n- Design and develop scalable data pipelines using Azure Data Factory, Azure Databricks, and related services.\n\n- Build and optimize data transformations using Python and PySpark.\n\n- Develop and manage SQL-based data models for reporting and analytics.\n\n- Integrate multiple data sources (ERP, Sales, External data feeds, etc.) into unified analytical models.\n\n- Implement data quality checks, validation frameworks, and monitoring mechanisms.\n\n- Support Power BI dashboards with optimized backend data models.\n\n- Handle large-scale sales and inventory datasets with performance optimization.\n\n- Collaborate with business stakeholders to understand sales and inventory KPIs.\n\nSecondary Responsibilities : \n\n- Implement pipelines for data engineering workflows.\n\n- Support data governance, access control, and security best practices.\n\n- Optimize cost and performance across Azure data services.\n\n- Provide technical documentation and support knowledge transfer.\n\n- Work closely with BI developers and ML engineers for advanced analytics use cases.\n\n- Support UAT, production deployment, and post-production monitoring.\n\nRequired Technical Skills : \n\n- Strong hands-on experience with Azure Fabric, Synopses, and Data Factory.\n\n- Azure Databricks (PySpark) development expertise.\n\n- Azure Data Lake (ADLS Gen2) knowledge.\n\n- Proficiency in Python and PySpark.\n\n- Strong SQL skills (performance tuning, query optimization).\n\n- Experience working with large sales and inventory datasets.\n\n- Data modeling for analytics and reporting (Star/Snowflake schema).\n\n- Experience with Power BI backend data optimization.\n\nSoft Skills : \n\n- Strong communication and stakeholder management skills.\n\n- Ability to work in a fast-paced, client-facing environment.\n\n- Strong problem-solving and analytical thinking capability.\n\n- Ability to manage timelines and deliverables independently.\n\nMandatory Requirements : \n\n- Please note that the below requirements are mandatory for the DKSH project.\n\n- Minimum 6+ years of experience in Data Engineering.\n\n- Hands-on experience working with Microsoft Fabric is mandatory.\nSkills\nMicrosoft Fabric, Azure Data Factory, Azure Databricks, Python, PySpark, SQL, Data Engineering, Data Validation","description_format":"text","description_chars":2906,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","AI Consulting & Integration","Enterprise Apps Implementation 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