{"id":4312697,"url":"https://alion.io/job/intraedge-senior-data-engineer-etl-pipelines","title":"Senior Data Engineer - ETL Pipelines","company":{"id":62138,"name":"IntraEdge","domain":"intraedge.com","url":"https://alion.io/company/intraedge","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","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":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"GCP","optional":true},{"name":"Hadoop","optional":true},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-14T11:57:10Z","employer_posted_date":null,"last_verified_at":"2026-11-14T11:57:10Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"About the Role:\n\nWe are looking for an experienced Senior Data Engineer with strong expertise in designing, developing, and optimizing enterprise-scale ETL/ELT pipelines and data integration solutions.\n\nKey Responsibilities:\n\n- Design, develop, and maintain scalable ETL/ELT pipelines for extracting, transforming, and loading data from multiple source systems.\n\n- Build robust data ingestion and integration frameworks to process structured and unstructured data.\n\n- Develop and optimize complex SQL queries, stored procedures, and data transformation logic.\n\n- Design and manage automated data workflows using Apache Airflow.\n\n- Implement batch and incremental data processing solutions to handle large volumes of enterprise data.\n\n- Develop and maintain data models, data warehouses, and data processing frameworks.\n\n- Monitor pipeline execution, troubleshoot failures, and optimize performance and resource utilization.\n\n- Implement data validation, reconciliation, and quality checks to ensure accuracy and consistency.\n\n- Collaborate with data architects, analysts, business stakeholders, and engineering teams to understand data requirements.\n\n- Establish best practices for data pipeline development, code quality, documentation, and deployment.\n\n- Support production data pipelines, resolve technical issues, and perform root cause analysis.\n\n- Provide technical guidance and mentorship to junior data engineers.\n\nRequired Skills & Qualifications:\n\n- 10 - 12 years of experience in Data Engineering, ETL Development, or Data Integration.\n\n- Strong hands-on experience designing and developing enterprise-scale ETL/ELT pipelines.\n\n- Advanced proficiency in SQL, including complex queries, joins, stored procedures, and query optimization.\n\n- Strong experience with Apache Airflow for workflow orchestration, scheduling, and pipeline monitoring.\n\n- Experience building data ingestion, transformation, and processing frameworks.\n\n- Strong understanding of data warehousing concepts, dimensional modelling, and database architecture.\n\n- Experience handling large datasets and complex data transformations.\n\n- Knowledge of batch processing, incremental data loading, and data integration patterns.\n\n- Experience with data quality, validation, reconciliation, and pipeline monitoring.\n\n- Familiarity with version control systems such as Git and software development best practices.\n\n- Strong analytical, troubleshooting, and problem-solving abilities.\n\nGood to Have:\n\n- Programming experience in Python or PySpark.\n\n- Exposure to cloud-based data platforms such as AWS, Azure, or GCP.\n\n- Familiarity with Snowflake, Databricks, Redshift, or similar data warehouse platforms.\n\n- Experience with DBT or other data transformation frameworks.\n\n- Knowledge of big data technologies such as Apache Spark and Hadoop.\n\n- Experience implementing CI/CD practices for data engineering workflows.\n\nPreferred Candidate Profile:\n\n- Strong technical ownership of end-to-end data engineering solutions.\n\n- Ability to work with cross-functional teams and translate business requirements into technical solutions.\n\n- Experience reviewing code, defining engineering standards, and mentoring team members.\n\n- Strong communication and stakeholder coordination skills.\n\nSkills\nData Engineering, ETL, SQL, Apache Airflow, Data Warehousing, Python, PySpark, Databricks, Snowflake DB, Data Modeling","description_format":"text","description_chars":3376,"description_truncated":false,"requirements":{"experience_years_min":10,"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":["Custom Software Development","IT Staffing & Staff Augmentation","IT Training & Certification"],"lifecycle":[{"event":"open","at":"2026-11-14T13:10:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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