Intern, Data Engineer

Acxiom

. Support the design, development, and optimization of modern data platforms for analytics, experimentation, and AI-driven workflows .

Posted 9/15/2026part-timeRemote • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in SQL and Python for data manipulation and transformation, with foundational knowledge of ETL/ELT processes and cloud platforms. Capable of supporting data pipeline development and optimization for analytics and AI workflows while adhering to data governance and privacy best practices.

Highest-signal resume keywords

SQL ProficiencyPython ScriptingETL/ELT WorkflowsCloud Platform ExposureData Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonETLELTData PipelinesData LakesData WarehousesData Quality ChecksData TransformationAI/ML Pipelines

Soft Skills

CollaborationClear CommunicationAttention to DetailWillingness to Learn

Tools & Technologies

SparkDatabricksSnowflakeApache AirflowGitCI/CD WorkflowsAWSAzureGCPKafka

Industry Keywords

Data GovernanceData PrivacyPIIGDPRCCPABatch ProcessingStreaming ProcessingData ModelingFeature EngineeringData Formats

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudETLGoogle Cloud PlatformKafkaPythonSparkSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Part-time internship schedule: 20–25 hours/week during the semester and up to 40 hours/week during breaks