{"id":1252917,"url":"https://alion.io/job/aventure-innovations-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3806694,"name":"Aventure Innovations","domain":"aventuresolution.com","url":"https://alion.io/company/aventure-innovations","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":21000,"max_usd":44000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"CloudFormation","optional":true},{"name":"dbt","optional":true},{"name":"Rest API","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-11T11:58:29Z","employer_posted_date":null,"last_verified_at":"2026-09-11T11:58:29Z","board_verified":false,"closed_at":null,"days_open":20,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":20},"description":"Hiring Senior Data Engineer - Databricks | PySpark | Spark | Delta Lake | AWS/Azure\n\nTotal Experience : 7-9 years\n\nAbout the Role : \n\nWe are looking for a hands-on Senior Data Engineer / Databricks Engineer who can build scalable, reliable and high-performance data pipelines using Databricks, Apache Spark, PySpark, Python and SQL.\n\nYou will play a key role in designing and delivering modern Lakehouse, ETL/ELT and data engineering solutions, transforming business requirements into production-ready pipelines, Delta Lake tables and reusable data components.\n\nThis is an opportunity for a strong Data Engineer who enjoys solving complex data problems, optimizing Spark workloads and building production-grade data platforms across AWS or Azure.\n\nKey Responsibilities : \n\n- Design, develop and maintain scalable ETL/ELT data pipelines using Databricks, Spark and PySpark.\n\n- Build and manage production-grade Delta Lake tables and Lakehouse data solutions.\n\n- Translate business and technical requirements into robust, reusable and maintainable data engineering solutions.\n\n- Develop high-quality Python, SQL and PySpark code for large-scale data processing.\n\n- Optimize Apache Spark / PySpark jobs for performance, scalability and cloud cost efficiency.\n\n- Implement Databricks Workflows for reliable data pipeline orchestration and scheduling.\n\n- Apply Unity Catalog best practices for data governance, security and access management.\n\n- Develop reusable data engineering frameworks, reference patterns and components.\n\n- Work with Databricks SQL and modern Lakehouse architecture.\n\n- Support AI/ML data pipelines, model development workflows and production data requirements.\n\n- Integrate data from multiple sources, including APIs and cloud-based systems.\n\n- Collaborate with Data Scientists, ML Engineers, Software Engineers and business stakeholders.\n\n- Troubleshoot pipeline failures, data quality issues and performance bottlenecks.\n\n- Follow engineering best practices for testing, documentation, version control and deployment.\n\n- Contribute to DevOps / MLOps practices and infrastructure automation where required.\n\nRequired Skills & Qualifications : \n\n- Bachelor's degree in Computer Science, Engineering, Information Technology or a related field.\n\n- 7+ years of experience in Software Engineering, Data Engineering or a related technical discipline.\n\n- Strong programming skills in Python, SQL, and PySpark.\n\n- Strong understanding of ETL / ELT pipeline development.\n\n- Hands-on experience with Delta Lake and Databricks Lakehouse architecture.\n\n- Good knowledge of AWS or Microsoft Azure cloud platforms.\n\n- Strong understanding of Data Warehousing and Lakehouse architecture.\n\n- Experience building scalable data pipelines and processing large datasets.\n\n- Strong understanding of data engineering concepts, data modeling and pipeline optimization.\n\nPreferred Skills : \n\n- Experience with Databricks Workflows, Databricks SQL, and dbt (Data Build Tool).\n\n- Experience supporting AI/ML pipelines and MLOps / DevOps practices.\n\n- Experience with Terraform or AWS CloudFormation.\n\n- Strong understanding of REST APIs / API-based data ingestion.\n\n- Experience with CI/CD and automated deployment pipelines.\n\n- Knowledge of cloud-native data engineering and modern data platforms.\n\nSkills\nPySpark, Databricks, Data Engineering, AWS, ETL, Data Pipeline, DataLake, Python, SQL, Data Warehousing","description_format":"text","description_chars":3404,"description_truncated":false,"requirements":{"experience_years_min":7,"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":"2026-09-25T18:04:06Z"}],"liveness":{"score":45,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.708,"p_room":0.75,"age_days":19,"expected_fill_days":24,"reasons":["seen:19","velocity","win:late"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/aventure-innovations-senior-data-engineer","json_url":"https://alion.io/job/aventure-innovations-senior-data-engineer.json","meta":{"generated_at":"2026-10-02T02:40:57Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3627,"day_limit":5000,"remaining_today":1373,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}