Minimum 5+ years of hands-on experience in data engineering Expertise in building data pipelines and ETL processes using DataBricks, dbt, and Python Extensive experience with PurView a plus.

Hands-on experience with data flow and pipeline frameworks such as Kafka, NiFi, Spark, Airflow, and Hadoop. Hands-on experience with one or more database technologies (e.g., PostgreSQL, Oracle, MySQL, SQL Server, DB2, MongoDB, Neo4j, Couchbase, Cassandra.

Demonstrated experience building data pipelines with PySpark and AWS. Application development experience in financial services with hands on designing, developing, and deploying complex applications.

2+ years of hands-on experience with data science and analytics, modeling platforms, data engineering software and visualization tools (e.g. Advanced SQL, PL/SQL, R, Python, SAP HANA, Spotfire, Tableau, Hadoop, Redshift.

As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting. Being a domain expert on data modeling, data pipelines, data quality and data warehousing of financial data.

Required Skills Strong hands-on experience Informatica Enterprise Data Catalog, Axon and Data Engineering Integration. 5 + years of Experience working with Informatica Enterprise Data Catalog, Axon and Data Engineering Integration.

Hands-on experience designing and implementing Platform core services around Compute, Storage, Networking, Databases, Containers, Security, Identity, etc. Hands-on experience with IaC tools such as Terraform, Ansible, ARM, CloudFormation.

As a leader in digital financial services, our customer and employee experiences run on data. We're looking for a passionate Principal Data Scientist with hands-on predictive modeling experiences and in-depth knowledge of consumer lending products.

Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, AutoScaling, CloudFormation, LakeFormation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, Cloudtrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.

2+ years of professional data engineering experience. Collaborating on the design, deployment and continuous improvement of a scalable data platform that ingests, stores, and aggregates various datasets.

UES provides essential engineering services for some of the most prominent and significant projects in the nation. With some of the greatest talent in Geotechnical Engineering, Construction Materials Testing and Inspection, Code Compliance, Environmental, Occupational Health & Safety, and Building Envelope, we are committed to delivering groundbreaking solutions for our clients.

Must have experience on ETL development life cycle, best practices of ETL pipelines, thorough work experience on data warehouse using combination of Python, Snowflake & AWS ServicesData engineering experience with AWS Services (S3, Lambda, Glue, Lake Formation, EMR), Kafka, Streaming, Databricks is highly preferred.

Strong hands-on experience Informatica Enterprise Data Catalog, Axon and Data Engineering Integration. Experience working with Power Exchange DB2 on Zos, creating lineage with custom SQL or any other data integration engines.

Hands on Data Engineering Manager. As a Hands-On Engineering Manager, you will play a pivotal role in leading our small but highly skilled engineering team to drive technological innovation and support our rapid growth trajectory.

This role will perform hands-on delivery of solutions that include artificial intelligence (AI) and cognitive services, ML models, pipelines, databases, and other data analytics components, contributing to the development and unit testing of solutions.