{"id":2810225,"url":"https://alion.io/job/millenniumit-esp-senior-engineer-data-engineering-analytics","title":"Senior Engineer – Data Engineering & Analytics","company":{"id":2563097,"name":"MillenniumIT ESP","domain":"mitesp.com","url":"https://alion.io/company/mitesp","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","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":["Colombo, Sri Lanka"],"countries":["LK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12500,"max_usd":32000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2491},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Informatica","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Oracle","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"Terraform","optional":false},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-10-18T09:21:37Z","employer_posted_date":"2026-10-18","last_verified_at":"2026-10-21T16:47:05Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Job Description\nDesign, build, and maintain scalable batch and real-time ETL/ELT pipelines on enterprise data platforms, including Databricks, Snowflake, Microsoft Fabric, Cloudera, Informatica IDMC, and Oracle\nDevelop lakehouse and data warehouse solutions using Medallion (Bronze/Silver/Gold) architecture on Delta Lake, Apache Iceberg, OneLake, Snowflake, and Oracle Autonomous Data Warehouse (ADW)\nBuild and orchestrate data workflows using Databricks Lakeflow, Fabric Data Factory, Azure Data Factory, Informatica Cloud Data Integration, Snowflake Streams & Tasks, and Apache Airflow\nImplement Change Data Capture (CDC) and streaming ingestion using Oracle GoldenGate, Apache Kafka, and Spark Structured Streaming\nApply dimensional data modelling, including Kimball star schemas, to deliver analytics-ready data marts\nDevelop Power BI semantic models, including Direct Lake, DAX, and row-level security, in partnership with BI and analytics teams\nImplement data governance, security, data quality, and lineage using Databricks Unity Catalog, Microsoft Purview, Cloudera SDX, and Informatica Data Quality\nPrepare governed, high-quality data for AI and Machine Learning use cases, including feature pipelines and RAG-ready datasets using vector search capabilities on Databricks, Snowflake Cortex, and Oracle AI Vector Search\nApply DataOps practices, including Git-based version control, CI/CD for data pipelines, automated testing, and Infrastructure as Code\nMonitor, troubleshoot, and optimize production pipelines for performance and cloud cost, supporting the practice's 99.90% uptime SLA commitment\nWork directly with client stakeholders across the delivery lifecycle, including requirements gathering, data model validation, UAT, Go-Live, and post-Go-Live SLA support\nMentor junior engineers and contribute to internal engineering standards, reusable pipeline frameworks, and technical documentation\nPerson Specification\nPossess a Bachelor's Degree in Data Science or a higher qualification, such as an MSc in Data Science, Data Engineering, or Artificial Intelligence, from a recognized university\nHave 2-5 years of professional experience in building and operating enterprise data pipelines, data warehouses, or lakehouses\nPossess hands-on experience with at least two of the following platforms: Databricks, Snowflake, Microsoft Fabric/Azure Data Services, Cloudera, Informatica (IDMC/PowerCenter), or Oracle (ADW/Exadata/ODI)\nDemonstrate strong experience with Apache Spark and distributed data processing at scale\nPossess a solid understanding of data modelling, data quality, and data governance principles\nHave experience developing Power BI semantic models and reports\nDemonstrate strong communication skills and the ability to work directly with client stakeholders\nProfessional certifications such as Databricks Certified Data Engineer (Associate/Professional), SnowPro Core or SnowPro Advanced: Data Engineer, Microsoft Certified: Fabric Data Engineer Associate (DP-700) or Fabric Analytics Engineer Associate (DP-600), Informatica IDMC, or Oracle Autonomous Database certifications will be considered an added advantage\nExperience in migrating legacy ETL platforms such as Informatica PowerCenter, SSIS, or ODI, or on-premises data warehouses to modern cloud lakehouse platforms will be considered an added advantage\nExperience with real-time streaming and CDC tools, including Kafka and Oracle GoldenGate, will be considered an added advantage\nExposure to GenAI data engineering, including RAG pipelines, vector databases, and LLM-ready data preparation, will be considered an added advantage\nExperience with dbt, Terraform, Azure DevOps, or GitHub Actions will be considered an added advantage\nPrior experience in banking, telecommunications, or public-sector data projects will be considered an added advantage\nDemonstrate strong SQL and Python (PySpark) skills; knowledge of Scala or Java will be considered an added advantage","description_format":"text","description_chars":3951,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-18T09:21:37Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":2,"expected_fill_days":27,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-10-21T05:46:15Z"},"pay":null,"html_url":"https://alion.io/job/millenniumit-esp-senior-engineer-data-engineering-analytics","json_url":"https://alion.io/job/millenniumit-esp-senior-engineer-data-engineering-analytics.json","meta":{"generated_at":"2026-10-21T16:48:53Z","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":23722,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-22T00:00:00Z"}},"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":2563097},"rest":"https://alion.io/mcp/rest/get_company?id=2563097"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmillenniumit-esp-senior-engineer-data-engineering-analytics"},{"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%2Fmillenniumit-esp-senior-engineer-data-engineering-analytics"},{"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%2Fmillenniumit-esp-senior-engineer-data-engineering-analytics"},{"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/millenniumit-esp-senior-engineer-data-engineering-analytics\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmillenniumit-esp-senior-engineer-data-engineering-analytics"}]}