{"id":2233719,"url":"https://alion.io/job/air-arabia-data-engineer-ii","title":"Data Engineer II","company":{"id":1782912,"name":"Air Arabia","domain":"airarabia.com","url":"https://alion.io/company/airarabia-com","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":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":34000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":15},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"ITIL","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-10T20:42:28Z","employer_posted_date":null,"last_verified_at":"2026-10-10T20:42:28Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Job Purpose\n\nDesign and deliver robust, scalable data pipelines and infrastructure components that ensure reliable, high-quality data availability for analytics, data science, and AI workloads. The role operates with growing technical ownership, taking end-to-end responsibility for assigned platform domains and contributing meaningfully to architectural decisions and engineering standards.\n\nKey Result Responsibilities\n\nDesign, develop, and maintain scalable ETL/ELT pipelines that ingest, transform, and serve data from structured and unstructured sources across cloud environments\nOwn assigned pipeline domains end-to-end — from requirements and design through to deployment, monitoring, and iterative improvement\nImplement and evolve data models that support analytics, BI, and machine learning consumption requirements\nBuild and maintain orchestration workflows using tools such as Apache Airflow, dbt, or Azure Data Factory\nOptimize pipeline and query performance across cloud data platforms including Snowflake and Azure Synapse\nDefine and implement data quality rules, automated testing, and alerting to ensure reliability and consistency of data outputs\n\nKey Result Responsibilities-Continued\n\nContribute to architectural discussions and platform decisions, providing well-reasoned technical input and trade-off analysis\nCollaborate with Data Scientists, Analytics Engineers, and business stakeholders to translate data requirements into maintainable engineering solutions\nConduct code reviews and support the development of Associate and DE I engineers through practical guidance\nMaintain clear documentation for all assigned pipelines, data models, and infrastructure components\n\nQualifications (Academic, Training, Languages)\n\nBachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field. \nFluent in English Language.\nITIL Certification is an advantage but not mandatory.\nStrong proficiency in SQL and Python for data transformation, automation, and pipeline development.\nWorking knowledge of data orchestration and transformation tools (e.g., Apache Airflow, dbt).\nUnderstanding of data modelling techniques — dimensional modelling, star/snowflake schema, and medallion/lakehouse architecture patterns.\nFamiliarity with batch and streaming data processing concepts (e.g., Spark, Kafka, Azure Event Hubs).\nGood grasp of software engineering fundamentals: version control (Git), CI/CD practices, and automated testing.\nAbility to communicate technical designs clearly and provide constructive feedback to junior team members.\n\nWork Experience\n\nWith 4–6 years of hands-on experience in data engineering or a closely related software engineering role\nDemonstrable experience delivering production-grade data pipelines in a cloud environment.\nSolid hands-on experience with cloud data platforms on Azure, AWS, or GCP (e.g., Azure Data Factory, Synapse Analytics, S3, Redshift, BigQuery).\nExperience with data warehousing platforms such as Snowflake or Azure Synapse, including query optimisation and access 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now","p_open":1,"p_active":0.86,"p_room":1,"age_days":2,"expected_fill_days":19,"reasons":["seen:2","win:early"],"computed_at":"2026-10-13T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/air-arabia-data-engineer-ii","json_url":"https://alion.io/job/air-arabia-data-engineer-ii.json","meta":{"generated_at":"2026-10-13T08:58:48Z","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 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