{"id":2444201,"url":"https://alion.io/job/dentsu-senior-data-engineer-3","title":"Senior Data Engineer","company":{"id":888,"name":"dentsu","domain":"dentsu.com","url":"https://alion.io/company/dentsu-polska","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":145,"ghost_share":0.007,"stale_share":0.724,"repost_share":0.055,"time_to_fill_p50_days":22,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":32000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Airflow","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"BigQuery","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-10-13T13:04:05Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-14T03:02:30Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Description:\nJOB DESCRIPTIONS\nData Engineering Roles | Databricks & SQL Focus\nSENIOR DATA ENGINEER (5 Years Experience)\nPosition Overview\nWe are seeking a Data Engineer with 5 years of experience to develop and maintain robust data pipelines and analytics infrastructure. This role focuses on hands-on implementation using Databricks and SQL, contributing to data platform initiatives while continuously growing technical expertise in cloud-native data solutions.\nKey Responsibilities\nDevelop and deploy ETL/ELT pipelines using Databricks, PySpark, and SQL for data ingestion, transformation, and loading\nWrite clean, efficient SQL and Python code for data processing, validation, and analytics\nSupport data pipeline maintenance, monitor job executions, and troubleshoot data quality issues within SLA timelines\nCollaborate with Senior Engineers, Data Scientists, and Analytics teams to understand requirements and deliver solutions\nImplement data validation, error handling, and logging mechanisms to ensure pipeline reliability\nDocument code, architecture decisions, and runbooks for operational excellence\nParticipate in code reviews and contribute to knowledge sharing within the engineering team\nRequired Skills & Experience\n5+ years of professional experience in data engineering, ETL development, or data analytics engineering\nStrong proficiency in Databricks (Spark SQL, PySpark) with real-world pipeline development experience\nSolid SQL skills including query optimization, joins, aggregations, and window functions\nHands-on experience with Python for data processing and scripting\nExperience with cloud platforms such as Azure Data Factory, AWS Glue, or similar ETL services\nUnderstanding of data architecture, data modeling, and relational databases\nStrong problem-solving skills with attention to data quality and accuracy\nRequired Certifications (Nice to Have)\nDatabricks Certified Data Engineer (Associate) OR\nSnowflake SnowPro Core Certified OR\nAWS Certified Data Engineer (Associate) OR equivalent professional data engineering certification\nPreferred Qualifications\nExperience with orchestration tools (Apache Airflow, Tidal, Control-M, etc.)\nFamiliarity with cloud data warehousing (Snowflake, Redshift, BigQuery)\nExperience with Git, CI/CD pipelines, and version control\nKnowledge of Agile methodologies and experience working in cross-functional teams\nBackground in data validation frameworks and data quality testing\nLocation:\nDGS India - 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