Position Highlights
We are seeking a collaborative and detail-oriented Data Engineer to design, build, and optimize data platforms and workflows that power high-scale analytics, identity resolution, and privacy-compliant data sharing. This role involves working across cloud ecosystems such as Databricks, Snowflake, AWS, Azure, and GCP, with a focus on scalable ETL/ELT pipelines, data ingestion, transformation, and secure data sharing. You will play a pivotal role in enabling data-driven decision-making by ensuring reliable, well-modeled, and high-performance data infrastructure.

Key Responsibilities

Design and develop batch and streaming data pipelines using Spark, Databricks, Snowflake, and cloud-native tools.
Build and maintain ETL/ELT workflows using orchestration platforms like Apache Airflow, dbt, or cloud schedulers.
Ingest structured and semi-structured data from diverse sources (e.g., S3, ADLS, GCS, Kafka) into raw and curated data zones.
Implement data transformation, normalization, aggregation, and joining logic using SQL and Python.
Ensure data quality, accuracy, and integrity through robust design and support for automated validation and monitoring.
Collaborate with business & data analysts, data scientists, and QA engineers to align pipeline outputs with business and analytic needs.
Participate in developing and enforcing data modeling and governance standards (e.g., star/snowflake schema, data lineage, metadata tagging).
Build and support privacy-aware data-sharing mechanisms such as Snowflake Clean Rooms and Databricks Delta Sharing.
Monitor and optimize pipeline performance, scalability, and cost efficiency across cloud environments.
Document architecture, data flows, and transformation logic for auditability and team collaboration.
Integrate pipelines into CI/CD frameworks using GitHub Actions, Azure DevOps, or GitLab

Required Qualifications

Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field, or 0–2 years of relevant experience (including internships or academic projects) in data engineering, ETL development, or related areas.
Proficiency in SQL with the ability to handle complex joins, aggregations, and window functions.
Familiarity with data formats like Parquet, Avro, JSON, and Delta Lake.
Working knowledge of Python for scripting, data transformation, or pipeline development.
Understanding of cloud data platforms such as AWS (S3, Glue), Azure (Data Lake, Synapse), or GCP (BigQuery, Dataflow).
Exposure to batch and streaming architectures, and awareness of their trade-offs.
Good documentation and collaboration skills with a growth mindset and attention to detail

Preferred Qualifications

Hands-on experience with Apache Airflow, dbt, or other workflow orchestration tools.
Experience developing in Databricks notebooks or Snowflake SQL worksheets.
Familiarity with distributed computing frameworks such as Apache Spark or Delta Live Tables.
Understanding of data governance frameworks and metadata management tools (e.g., Alation, Collibra).
Interest in identity resolution, data tokenization, and secure multi-party data collaboration.
Knowledge of data privacy regulations such as GDPR or CCPA and best practices for secure data sharing

Location

Remote, Continental US (Preferably in Texas or Arkansas)

Primary Location City/State:

Homebased - Conway, Arkansas

Additional Locations (if applicable):

Acxiom is an equal opportunity employer, including disability and protected veteran status (EOE/Vet/Disabled) and does not discriminate in recruiting, hiring, training, promotion or other employment of associates or the awarding of subcontracts because of a person's race, color, sex, age, religion, national origin, protected veteran, military status, physical or mental disability, sexual orientation, gender identity or expression, genetics or other protected status.

Attention California Applicants: Please see our CCPA/CPRA Privacy Act notice

here

Attention Colorado, California, Connecticut, Maryland, Nevada, New Jersey, New York City, Ohio, Rhode Island, and Washington Applicants: This position is not located in the aforementioned locations but applications for remote work may be considered. For information about this role under state or local equal pay or pay transparency laws, please contact

recruit@acxiom.com

Acxiom

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