{"id":2975172,"url":"https://alion.io/job/fugentex-solutions-data-engineer","title":"Data Engineer","company":{"id":3806667,"name":"FuGenTex Solutions","domain":"fugentex.com","url":"https://alion.io/company/fugentex-solutions","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"WP Job Openings","truth_index":{"grade":"D","score":53,"open_postings":117,"ghost_share":0.778,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"freelance","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_cell","sample_n":77},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"CI/CD","optional":true},{"name":"CloudFormation","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"Power BI","optional":true},{"name":"Rest API","optional":true},{"name":"Scrum","optional":true},{"name":"Tableau","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-07-04T05:55:09Z","employer_posted_date":"2026-07-04","last_verified_at":"2026-10-22T09:49:30Z","board_verified":true,"closed_at":null,"days_open":110,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":109},"description":"Job Summary\nWe are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and data platforms that support analytics, reporting, and machine learning initiatives. The ideal candidate will have experience working with large-scale data processing, cloud-based data solutions, ETL/ELT frameworks, and modern data warehousing technologies.\nKey Responsibilities\nDesign, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources.\nBuild and optimize data architectures, data lakes, and data warehouses for structured and unstructured data.\nDevelop and manage batch and real-time data processing pipelines.\nCollaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality data solutions.\nOptimize SQL queries, data models, and pipeline performance to ensure efficient data processing.\nEnsure data quality, integrity, security, and governance across all data platforms.\nImplement data validation, monitoring, and troubleshooting processes.\nWork with cloud-based data services and modern data engineering tools.\nDevelop and maintain technical documentation for data pipelines, workflows, and architecture.\nSupport data migration and integration projects involving multiple enterprise systems.\nParticipate in code reviews and follow best practices for data engineering and DevOps.\nRequired Skills\nStrong programming experience in Python, SQL, and/or Scala.\nHands-on experience with ETL/ELT tools and frameworks.\nStrong knowledge of relational databases and data modeling concepts.\nExperience with modern data warehouses such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.\nExperience building data pipelines using Apache Spark, PySpark, or similar distributed processing frameworks.\nKnowledge of workflow orchestration tools such as Apache Airflow or Azure Data Factory.\nExperience working with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).\nFamiliarity with data lakes, data governance, and data quality best practices.\nExperience with Git and version control.\nStrong analytical, troubleshooting, and problem-solving skills.\nPreferred Skills\nExperience with streaming technologies such as Apache Kafka, Azure Event Hubs, or Amazon Kinesis.\nKnowledge of Databricks and Delta Lake.\nExperience with Infrastructure as Code (Terraform, ARM, or CloudFormation).\nUnderstanding of DevOps and CI/CD pipelines for data engineering.\nExposure to Machine Learning data pipelines and feature engineering.\nExperience with REST APIs and third-party data integrations.\nTechnical Skills\nPython\nSQL\nPySpark / Apache Spark\nApache Airflow\nAzure Data Factory (ADF)\nAzure Synapse Analytics\nSnowflake\nDatabricks\nAzure Data Lake Storage (ADLS)\nAWS S3 / Amazon Redshift\nGoogle BigQuery\nApache Kafka\nGit\nDocker (Preferred)\nQualifications\nBachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.\nRelevant certifications in Azure, AWS, GCP, or Snowflake are preferred.\nPreferred Experience\n5-8 years of experience in Data Engineering.\nExperience designing and implementing enterprise-scale data pipelines.\nHands-on experience with cloud-based data platforms and modern data architectures.\nExperience working in Agile/Scrum environments.\nNice to Have\nExperience supporting AI/ML workloads and data pipelines.\nKnowledge of Data Mesh, Data Fabric, or Lakehouse architecture.\nFamiliarity with Power BI, Tableau, or other BI tools.\nExperience with data governance frameworks and metadata management tools.\nExposure to Generative AI data preparation and vector databases.\nWhat We Offer\nOpportunity to work on enterprise-scale cloud and data transformation projects.\nExposure to modern data engineering technologies and cloud platforms.\nCollaborative and innovation-driven work environment.\nCareer growth and learning opportunities.\nCompetitive compensation and comprehensive benefits.\nFlexible work arrangements (Remote/Hybrid, based on business 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