Intern, Data Engineer
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Job Description
Data Engineer Intern supporting Acxiom’s cloud data platforms, ETL pipelines, and AI-driven workflows. Gaining hands-on experience with SQL, Python, Spark, and cloud services.
Responsibilities:
- Support the design, development, and optimization of modern data platforms for analytics, experimentation, and AI-driven workflows
- Assist in building and maintaining batch and streaming data pipelines using Spark, Databricks, Snowflake, and cloud-native services
- Support ETL/ELT workflows using Apache Airflow, dbt, or managed cloud schedulers
- Help ingest structured and semi-structured data from S3, ADLS, GCS, APIs, or Kafka into raw and curated data layers
- Write and maintain SQL and Python transformations for cleaning, joining, and aggregating datasets
- Participate in data quality checks, validation rules, and basic monitoring
- Collaborate with data engineers, analysts, data scientists, and AI practitioners
- Prepare datasets and feature tables for AI/ML pipelines and autonomous agents
- Explore AI-agent interactions with data platforms, including querying data, triggering pipelines, and summarizing results
- Document data flows, schemas, and pipeline logic
- Learn and follow data modeling, governance, and privacy best practices
- Support version control and deployment using Git and basic CI/CD workflows
Requirements:
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related field
- Basic proficiency in SQL, including simple joins, aggregations, and filtering
- Familiarity with Python for scripting, data manipulation, or coursework projects
- Introductory understanding of ETL/ELT, data lakes, and data warehouses
- Exposure to at least one cloud platform: AWS, Azure, or GCP
- Interest in AI, machine learning, or intelligent systems
- Strong willingness to learn, ask questions, and collaborate in a team environment
- Clear written and verbal communication skills with attention to detail
- Anticipated graduation date between May 2027 and December 2027
- Preferred: project experience with Databricks, Snowflake, or BigQuery
- Preferred: exposure to Apache Spark, dbt, or workflow orchestration tools
- Preferred: familiarity with Parquet, JSON, Avro, or Delta Lake
- Preferred: basic understanding of streaming versus batch processing
- Preferred: coursework or projects involving AI agents, LLMs, or ML pipelines
- Preferred: awareness of data privacy concepts such as PII, GDPR, or CCPA
- Preferred: experience with GitHub or similar version control systems
Benefits:
- Part-time internship schedule: 20–25 hours/week during the semester and up to 40 hours/week during breaks
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