{"id":1279292,"url":"https://alion.io/job/xome-lead-data-engineer","title":"Lead Data Engineer","company":{"id":2840605,"name":"Xome","domain":"xome.com","url":"https://alion.io/company/xome-com","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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India","Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Data 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Lake","optional":true},{"name":"GCP","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-25T07:45:18Z","employer_posted_date":null,"last_verified_at":"2026-08-25T07:45:18Z","board_verified":false,"closed_at":null,"days_open":52,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":52},"description":"Role : Lead Data Engineer\n\nExperience : 10 - 12 yrs\n\nLocation : Chennai / Bangalore\n\nResponsibilities : \n\n- Design and build scalable, reliable data pipelines and ETL/ELT workflows across batch and near-real-time processing scenarios.\n\n- Develop and maintain data models across relational (SQL Server) and NoSQL (MongoDB, Atlas) systems to support analytical and operational use cases.\n\n- Build and manage data solutions on Microsoft Fabric including Lakehouses, Warehouses, Dataflows, and Pipelines to deliver a unified analytics platform.\n\n- Drive AI-enabled development practices within the team leveraging AI coding assistants, LLM-based tools, and intelligent automation to accelerate pipeline development, improve code quality, and reduce manual effort.\n\n- Lead, mentor, and grow a team of data engineers; conduct code reviews, provide technical guidance, and support career development.\n\n- Collaborate with stakeholders, product owners, data scientists, and analysts to understand data needs and translate them into engineering solutions.\n\n- Build and maintain Power BI data models, semantic layers, and datasets to support self-service analytics and business reporting.\n\n- Continuously identify opportunities to optimize pipeline performance, reduce costs, and improve data reliability and quality.\n\n- Adhere to and enforce data engineering standards, data security, and governance practices across the platform.\n\nRequired Skills and Experience : \n\n- 8 to 10 years of experience in data engineering with a strong track record of delivering production-grade data solutions.\n\n- Strong proficiency in Python (PySpark, Pandas) and SQL for data transformation, pipeline development, and performance tuning.\n\n- Proficient with Microsoft Fabric including Lakehouses, Warehouses, Dataflows Gen2, and Data Pipelines.\n\n- Strong experience with SQL Server including schema design, stored procedures, indexing, and query optimization.\n\n- Experience with MongoDB and MongoDB Atlas for NoSQL data modeling, indexing, aggregation pipelines, and Atlas Search.\n\n- Solid experience designing and operating ETL/ELT pipelines in production, including error handling, monitoring, and SLA management.\n\n- Familiarity with containerization using Docker and orchestration with Kubernetes for deploying and managing data workloads.\n\n- Experience with Power BI including dataset design, DAX, semantic modeling, and enabling self-service reporting.\n\n- Strong exposure to AI-enabled development using AI coding assistants, prompt-driven development, or LLM-integrated tooling to build and accelerate data engineering workflows.\n\n- Experience leading or managing a small team of engineers task allocation, mentoring, and performance support.\n\n- Good understanding of data modeling concepts dimensional modeling, star/snowflake schemas, data vault.\n\n- Ability to communicate technical ideas clearly to both technical and non-technical audiences.\n\nNice to Have Qualities & Skills : \n\n- Hands-on experience with Databricks including Delta Lake, notebooks, jobs, clusters, and Unity Catalog.\n\n- Exposure to cloud data services on Azure (preferred), GCP, or AWS.\n\n- Experience with streaming and event-driven architectures using Apache Kafka, Azure Event Hubs, Azure Service Bus, or similar queue/messaging technologies.\n\n- Exposure to .NET for building data-adjacent services or APIs.\n\n- Familiarity with data governance, data cataloging, and data lineage tooling.\n\n- Exposure to MLOps or supporting ML pipeline infrastructure.\n\n- Exposure to Mortgage or Real Estate domain.\nSkills\nData Engineering, Data Pipeline, ETL, SQL, Data Modeling, AI Integration, Microsoft Fabric, Python, Power BI, DAX Power BI, Data Services","description_format":"text","description_chars":3693,"description_truncated":false,"requirements":{"experience_years_min":10,"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":[],"lifecycle":[{"event":"open","at":"2026-09-26T02:00:24Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long 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