{"id":3079367,"url":"https://alion.io/job/fractal-cloud-engineer-ii","title":"Cloud Engineer II","company":{"id":226,"name":"Fractal","domain":"fractal.ai","url":"https://alion.io/company/fractal-analytics","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":43,"ghost_share":0,"stale_share":0.93,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-30T05:48:23Z"}},"role":"DevOps","role_family":"DevOps","seniority":"middle","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":11000,"max_usd":31000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":30},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","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":"Java","optional":false},{"name":"Matillion","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Talend","optional":false},{"name":"Apache Kafka","optional":true}],"status":"live","first_seen_at":"2026-10-22T11:35:15Z","employer_posted_date":null,"last_verified_at":"2026-10-22T11:35:15Z","board_verified":false,"closed_at":null,"days_open":8,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":8},"description":"As a Cloud Engineer II, you will be responsible for designing, building, and maintaining large-scale cloud-based data systems and infrastructure. You will develop data pipelines, implement data quality measures, and optimize systems to ensure efficient processing. This role involves collaborating with clients and stakeholders, translating business requirements into technical solutions, and applying best practices in cloud computing, data engineering, and security.\n\nResponsibilities: \nShowcase strong analytical and problem-solving capabilities by consulting with clients and other stakeholders to understand business problems.\nDesign, store, process, and maintain large-scale data systems and related infrastructure.\nBuild data pipelines, implement data quality, develop data models, monitor, and optimize pipelines to minimize runtime while adhering to organizational and customer standards.\nDemonstrate strong conceptual understanding of data warehousing, ETL, data governance, security, cloud computing, and batch & real-time data processing.\nApply strong execution knowledge of data modeling, SQL/NoSQL databases, SDLC practices, unit testing, and functional programming.\nWork with Medallion architecture patterns.\nWork on at least one major cloud platform.\nExecute multiple end-to-end data engineering projects.\nManage conversations with client stakeholders, understand requirements, and translate them into technical outcomes.\n\nRequirements: \n2-4 years of relevant work experience.\nStrong proficiency in SQL.\nExperience working on any major cloud platform (AWS, Azure, or GCP).\nWorking knowledge of ETL/orchestration tools such as IICS, Talend, Matillion, Airflow, Azure Data Factory, AWS Glue, GCP Composer, etc.\nWorking knowledge of OLTP databases (Postgres, MySQL, SQL Server, etc. ).\nWorking knowledge of data warehouses such as Snowflake, Redshift, Azure Synapse, Hive, BigQuery, etc.\nProficient in at least one programming language used in data engineering, such as Python (or Scala/Rust/Java).\nStrong execution knowledge of data modeling (star schema, snowflake schema, fact/dimension tables).\nProficient in Spark and related applications like Databricks, GCP DataProc, AWS Glue, EMR, etc.\nExperience with code and SQL query optimization.\nStrong knowledge of version control systems such as Git and designing CI/CD pipelines for continuous delivery.\nUnderstanding of code optimization and security best practices.\nStrong problem-solving skills and ability to analyze problems to develop effective solutions.\nProficient in written and verbal communication.\nExercises independent judgment to determine the best course of action within established practices and procedures.\nGood to have: cloud certification at an architect level, knowledge of unit/functional/integration testing, Kafka and real-time streaming, and CI/CD pipeline familiarity.\nSkills\nAWS, Airflow, Azure, DataProc, Databricks, EMR, ETL, GCP, IICS, Matillion, Spark, Talend, 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