{"id":3167845,"url":"https://alion.io/job/gccxglobal-senior-data-engineer","title":"Senior Data Engineer","company":{"id":4442763,"name":"GCCX","domain":"gccxglobal.com","url":"https://alion.io/company/gccxglobal","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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Azure","optional":false},{"name":"Azure Cosmos DB","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Cortex","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Spanner","optional":false},{"name":"Java","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Postman","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Swagger","optional":false},{"name":"Feast","optional":true},{"name":"Feature Store","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prometheus","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-10-23T17:36:00Z","employer_posted_date":null,"last_verified_at":"2026-10-23T17:36:00Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Responsibilities: \nDesign and develop advanced data engineering solutions that enable data pipelines, visualisation, and analytical tools.\nArchitect and implement scalable data platforms across on-premises, cloud, and hybrid environments.\nBuild, optimise, and operate complex batch and real-time and near-real-time streaming data pipelines.\nBuild, optimise, and operate low-latency, sub-second APIs on highly scalable, fault-tolerant architectures.\nDesign and maintain high-throughput data pipelines to support agentic AI workloads and real-time multi-agent MCP orchestration.\nBuild and maintain enterprise-scale Graph Databases that power organisational knowledge graphs and connected data experiences.\nPerform data wrangling, exploration, and discovery across heterogeneous data sources to generate insights.\nLead development of large-scale data processing solutions using Databricks and Spark technologies.\nDesign and optimise relational, NoSQL, and analytical data models.\nContribute to team knowledge sharing and advancement of data engineering standards and capabilities.\nMentor engineers to strengthen technical skills, delivery quality, and professional growth.\nSupport project definition activities including estimation, planning, and scoping in partnership with management.\n\nRequirements: \nBachelor's Degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.\n5-8 years of hands-on experience designing, building, and supporting data engineering solutions.\nStrong experience developing and migrating data solutions across cloud platforms.\nDemonstrated technical leadership and mentoring experience.\nStrong analytical and problem-solving skills applied to complex data challenges.\nAbility to manage multiple concurrent initiatives with strong organisational and prioritisation skills.\nPassion for learning and applying new data and platform technologies.\n\nCore Data Engineering and Platforms: \nAdvanced experience designing and building complex data pipelines using Python and SQL.\nStrong experience with cloud platforms and services, including: Azure (Data Factory, Data Lake, Event Hub, Functions, Web Apps, Cosmos DB) or GCP (Google Spanner, BigQuery).\nDatabricks with PySpark/ Spark SQL/ Scala Spark, including cluster configuration, autoscaling, and performance optimisation (e. g., Photon).\nSnowflake data warehousing, including schema design (star/snowflake), query optimisation, and cost/performance tuning.\nExpertise in SQL, NoSQL, and relational database design and development.\n\nAPIs, Streaming and Integration: \nProficiency in designing and consuming RESTful APIs with secure authentication and authorisation (OAuth 2.0 JWT, API keys).\nExperience using Postman and Swagger/OpenAPI for API testing, documentation, and validation.\nWorking knowledge of message queuing, stream processing, and highly scalable big-data data stores.\n\nEngineering Practices: \nAdvanced knowledge of data pipeline development using Python and experience with languages such as SQL, DAX, Java, Scala, and/or Go.\nExperience performing root-cause analysis and using technology to solve complex business problems.\nExperience adopting AI-assisted development tools and building AI-powered agents or agentic workflows to automate engineering tasks, accelerate delivery, and enhance data platform capabilities.\nExperience with NL-to-SQL query generation using Databricks Genie and Snowflake Cortex to enable natural language access to data assets.\nHands-on experience with Unity Catalogue for data governance, fine-grained access control, and end-to-end data lineage.\nExperience developing AI-assisted dbt models, including AI-generated transformation logic, automated documentation, and intelligent testing.\nFamiliarity with AI-powered data quality tools for automated profiling, anomaly detection, and pipeline observability.\n\nNice to Have: \nExperience with Iceberg table design and optimisation.\nExperience with Unity Catalogue governance and security.\nCloud platform certifications such as Azure Certified Solutions Architect, Azure Cloud Practitioner, or MCSA.\nExperience contributing to enterprise data governance, security, or compliance initiatives.\nExperience with ML feature platforms (e. g., Feast, Tecton, or Databricks Feature Store) and vector database engineering (e. g., Pinecone, Weaviate, pgvector).\nExperience designing and operating streaming AI pipelines and applying MLOps practices to data engineering workflows.\nExposure to end-to-end ML pipeline ownership and real-time AI inference plumbing in production environments.\nSkills\nazure, bigquery, data engineer, data engineering, databricks, gcp, pyspark, python, snowflake, spanner, spark, sql","description_format":"text","description_chars":4702,"description_truncated":false,"requirements":{"experience_years_min":5,"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":"2026-10-23T17:36:00Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":27,"reasons":["seen:1","velocity","win:early"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/gccxglobal-senior-data-engineer","json_url":"https://alion.io/job/gccxglobal-senior-data-engineer.json","meta":{"generated_at":"2026-10-25T23:00:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":32405,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4442763},"rest":"https://alion.io/mcp/rest/get_company?id=4442763"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgccxglobal-senior-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fgccxglobal-senior-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fgccxglobal-senior-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/gccxglobal-senior-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgccxglobal-senior-data-engineer"}]}