{"id":3418962,"url":"https://alion.io/job/nexgen-tech-data-engineer-intern","title":"Data Engineer Intern","company":{"id":1220925,"name":"Nexgen Tech","domain":"nexgentech.ca","url":"https://alion.io/company/nexgentech","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":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Jupyter Notebook","optional":false},{"name":"MySQL","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Linux","optional":true},{"name":"Microsoft Fabric","optional":true},{"name":"Power BI","optional":true},{"name":"pySpark","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-28T17:17:59Z","employer_posted_date":null,"last_verified_at":"2026-10-28T17:17:59Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"About NexGen Tech Solutions\nNexGen Tech Solutions is a global IT services, AI engineering, and digital transformation company headquartered in Frisco, Texas, USA, with delivery operations across India and international markets.\nThe company specializes in Artificial Intelligence, Generative AI, Agentic AI, Cloud Computing, Data Engineering, Cybersecurity, and Enterprise Software Development.\nThrough its AI-focused platforms and engineering expertise, NexGen helps organizations design, develop, and deploy intelligent, scalable, and secure technology solutions across multiple industries.\nAt NexGen, we are committed to innovation, continuous learning, and developing next-generation AI-powered solutions that solve real-world business challenges.\n\nJob Summary\nWe are looking for an enthusiastic and technically curious Data Engineer Intern to join our Data Engineering team.\nThe ideal candidate should have a strong foundation in Python, SQL, databases, and data structures, along with a basic understanding of data pipelines, ETL/ELT processes, and cloud-based data technologies.\nAs a Data Engineer Intern, you will work closely with experienced Data Engineers, Cloud Engineers, and Data Analysts to develop, maintain, and optimize data pipelines and support modern data platforms.\nThis internship offers hands-on exposure to real-world data engineering projects, data integration, cloud technologies, and big data processing frameworks.\nKey Responsibilities\nAssist in designing, developing, testing, and maintaining data pipelines for structured and unstructured data.\nSupport data extraction, transformation, and loading (ETL/ELT) processes from multiple data sources.\nWrite and optimize SQL queries for data extraction, transformation, and analysis.\nDevelop Python scripts for data processing, automation, and data integration.\nAssist with data cleaning, validation, transformation, and quality checks.\nWork with relational databases and understand data modeling concepts.\nSupport the integration of data from APIs, databases, flat files, and cloud storage systems.\nGain exposure to cloud-based data engineering services on Azure, AWS, or Google Cloud.\nAssist in troubleshooting data pipeline failures and resolving data quality issues.\nSupport data warehouse and data lake development activities.\nCollaborate with Data Engineers, Analysts, and cross-functional teams to understand business and technical requirements.\nPrepare technical documentation for data pipelines, workflows, and development activities.\nFollow coding standards, version control practices, and data security guidelines.\nRequired Technical Skills\n1. Programming\nGood understanding of Python programming.\nFamiliarity with Python libraries such as Pandas and NumPy.\nKnowledge of programming fundamentals, data structures, and basic algorithms.\n2. SQL & Databases\nStrong foundational knowledge of SQL.\nUnderstanding of joins, aggregations, subqueries, and basic query optimization.\nFamiliarity with relational database systems such as MySQL, PostgreSQL, or SQL Server.\nBasic understanding of database design and normalization.\n3. Data Engineering Fundamentals\nUnderstanding of ETL and ELT concepts.\nBasic knowledge of data pipelines and data integration.\nFamiliarity with structured and semi-structured data formats such as CSV, JSON, and Parquet.\nUnderstanding of data cleaning, transformation, and validation techniques.\n4. Development Tools\nBasic knowledge of Git and version control.\nFamiliarity with Jupyter Notebook or Visual Studio Code.\nUnderstanding of REST APIs and data extraction methods.\nGood to Have Skills\nExposure to cloud platforms such as Microsoft Azure, AWS, or Google Cloud.\nBasic familiarity with Azure Data Factory (ADF), Azure Databricks, or Microsoft Fabric.\nUnderstanding of Apache Spark or PySpark.\nAwareness of data warehousing concepts and platforms such as Snowflake, Amazon Redshift, or Google BigQuery.\nFamiliarity with workflow orchestration tools such as Apache Airflow.\nBasic understanding of data lakes, lakehouse architecture, and Delta Lake.\nExposure to Power BI or other business intelligence tools.\nBasic knowledge of Linux commands and shell scripting.\nUnderstanding of data modeling concepts, including star and snowflake schemas.\nFamiliarity with Docker and CI/CD concepts.\nEducational Qualifications\nCurrently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or a related field.\nStrong analytical, logical reasoning, and problem-solving skills.\nBasic understanding of software development practices.\nGood written and verbal communication skills.\nWillingness to learn new technologies and work in a collaborative engineering environment.\nWhat You Will Learn\nDevelop and maintain production-oriented data pipelines under engineering supervision.\nGain hands-on experience with Python, SQL, and modern data engineering tools.\nUnderstand cloud-based data architectures and ETL/ELT workflows.\nLearn how data warehouses, data lakes, and lakehouse platforms operate.\nWork with real-world datasets and business use cases.\nUnderstand data quality, pipeline monitoring, and performance optimization.\nGain exposure to enterprise data engineering best 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