{"id":3681772,"url":"https://alion.io/job/akaike-senior-data-engineer","title":"Senior Data Engineer","company":{"id":4457962,"name":"Akaike","domain":"akaike.ai","url":"https://alion.io/company/akaike","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","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":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Multimodal AI","optional":false},{"name":"pySpark","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-08-07T06:55:55Z","employer_posted_date":"2026-08-07","last_verified_at":"2026-11-07T04:26:11Z","board_verified":true,"closed_at":null,"days_open":92,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":91},"description":"Data Engineer\nExperience: 2-4 years\nLocation: Bengaluru (Hybrid)\nAbout the Company\nAkaike Technologies is a fast-growing AI-first organization focused on building real-world, high-impact AI systems across industries. We work at the intersection of Generative AI, Multimodal AI, and Large-Scale ML Engineering, enabling enterprises to operationalize cutting-edge AI solutions at scale. We foster a culture of ownership, deep technical rigor, and continuous learning.\nExperience Pre-Requisite: 2-4 years of hands-on experience in Data Engineering, with strong exposure to Databricks (PySpark, Spark SQL) and Azure Data Services (ADF, ADLS, Azure SQL). Candidates must demonstrate real-world experience in designing, building, deploying, and optimizing scalable data pipelines end-to-end.\nJob Description: We are seeking a highly skilled Data Engineer to design, develop, and deploy scalable data solutions on Databricks and Azure Data Services. This role requires deep technical expertise in PySpark, SQL, Delta Lake, and Medallion Architecture, combined with strong problem-solving ability and collaboration skills.\nThe ideal candidate will take end-to-end ownership of data engineering workflows-from data ingestion and transformation to data modeling and governance-while ensuring performance, reliability, and security. You will work in a fast-paced, cloud-native environment, partnering with cross-functional teams to deliver production-grade data pipelines that enable advanced analytics and business insights.\nKey Responsibilities\n1. Design and Development\nDesign, develop, and deploy scalable data pipelines using Databricks (PySpark, Spark SQL), Azure Data Factory, and other Azure data services.\nImplement ETL/ELT processes to ingest, transform, and load data from diverse sources into data lakes and data warehouses.\nOptimize and tune data pipelines for performance, scalability, and cost efficiency.\n2. Data Processing\nWrite and optimize complex SQL queries for data extraction, transformation, and analysis.\nUtilize PySpark for large-scale data processing and advanced analytics.\nImplement data partitioning, bucketing, and indexing strategies for efficient data retrieval.\n3. Data Integration\nIntegrate data from multiple sources, including structured, semi-structured, and unstructured formats.\nWork with APIs, streaming data, and batch processing to ensure seamless data integration.\n4. Data Governance and Quality\nApply data governance practices to maintain data quality, consistency, and security.\nMonitor and troubleshoot data pipelines to ensure accuracy, availability, and reliability.\n5. Collaboration\nPartner with data scientists, analysts, and other stakeholders to understand requirements and deliver solutions.\nWork closely with DevOps teams to deploy and monitor data pipelines in production environments.\n6. Documentation\nDocument data pipelines, workflows, and processes for knowledge sharing and future reference.\nMaintain up-to-date documentation on data architecture and data models.\nMust Have Technical Skills: Databricks: Hands-on experience with Databricks for data processing, analytics, and Serverless SQL Warehouse, Unity Catalog, Lakehouse, and Medallion Architecture.\nAzure Data Services: Proficiency in Azure Data Factory, Azure Data Lake Storage, Azure SQL Database, and Key Vault.\nSQL: Strong expertise in writing and optimizing complex SQL queries.\nPySpark: Experience in using PySpark for data processing and transformation.\nETL/ELT: Solid understanding of ETL/ELT processes and tools.\nData Modeling: Knowledge of data modeling techniques and best practices.\nData Governance: Familiarity with data governance, data quality, and data security practices.\nMust Have Soft Skills: Communication: Ability to clearly articulate technical ideas to both technical and non-technical audiences, especially in client-facing discussions.\nProblem Solving: Strong analytical mindset with the ability to structure ambiguous problems and deliver actionable AI solutions quickly.\nOwnership & Bias for Action: Self-driven, accountable, and proactive in driving outcomes end to end.\nCollaboration: Empathy, active listening, and effective conflict resolution in cross-functional teams.\nRelevant to Have: Experience with Azure DevOps for CI/CD pipelines.\nKnowledge of Delta Live Tables (DLT) in Databricks.\nBenefits and Perks: Competitive compensation and ESOPs\nOpportunity to work on cutting-edge Generative AI and multimodal systems\nHigh visibility across teams and leadership\nSupport for continuous learning, certifications, and conference 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