Senior Data Engineer - AI Solutions

You’ll make an impact by:

·       Design, build, and maintain data pipelines that serve the needs of multiple stakeholders including software developers, data scientists, analysts, and business teams.

·       Ensure data pipelines are modular, resilient, and optimized for performance and low maintenance.

·       Collaborate with AI/ML teams to support training, inference, and monitoring needs through structured data delivery.

·       Implement ETL/ELT workflows for structured, semi-structured, and unstructured data using cloud-native tools.

·       Work with large-scale data lakes, streaming platforms, and batch processing systems to ingest and transform data.

·       Establish robust data validation, logging, and monitoring strategies to maintain data quality and lineage.

·       Optimize data infrastructure for scalability, cost-e_¯iciency, and observability in cloud-based environments.

·       Ensure compliance with governance policies and data access controls across projects..

Use your skills to move the world forward!

·       Bachelor’s degree in computer science, Information Systems, or a related field.

·       4+ years of experience designing and deploying scalable data pipelines in cloud environments.

·       Proficiency in Python, SQL, and data manipulation tools and frameworks (e.g., Apache Airflow, Spark, dbt, Pandas).

·       Practical experience with data lakes, data warehouses (e.g., Redshift, Snowflake, BigQuery), and streaming platforms (e.g., Kafka, Kinesis).

·       Strong understanding of data modeling, schema design, and data transformation patterns.

·       Experience working with AWS (Glue, S3, Redshift, Sagemaker) or Azure (Data Factory, Azure ML Studio, Azure Storage).

·       Familiarity with CI/CD for data pipelines and infrastructure-as-code (e.g., Terraform, CloudFormation).

·       Preferred Qualifications: Exposure to building data solutions that serve AI/ML pipelines, including feature stores and real-time data ingestion.

·       Familiarity with observability, data versioning, and pipeline testing tools.

·       Experience engaging with diverse stakeholders, gathering data requirements, and supporting iterative development cycles.

·       Background or familiarity with the Power, Energy, or Electrification sector is a strong plus.

·       Knowledge of security best practices and data compliance policies for enterprise-grade systems.