Data Automation Engineer

This role involves designing and implementing data automation solutions primarily on AWS, with integration to Azure services and Generative AI capabilities. The engineer will build scalable data pipelines and automation workflows to support analytics, reporting, and customer engagement platforms in a remote setting., * Design and implement scalable data automation workflows using AWS services, with integration to selected Azure data platforms where required

• Develop ETL/ELT processes to ingest, transform, and move data across various cloud data sources such as Amazon DynamoDB, SQL Server on AWS, and Azure SQL
• Design, develop, and support batch and near-real-time ingestion pipelines using Apache Spark, Kafka, Flume, and integrate with existing platforms such as Apache Solr
• Evaluate and apply Generative AI services and frameworks, including Amazon Bedrock, Azure OpenAI, Hugging Face, and LangChain, to prototype and evaluate AI-assisted capabilities
• Develop scalable data-processing solutions using Amazon EMR and containerized environments like AWS Fargate or Kubernetes
• Integrate customer-interaction data into analytical data stores for reporting and analytics
• Implement data solutions following security and compliance standards, including IAM, encryption, VPC, and role-based access control
• Support Agile DevOps processes through sprint-based development of pipeline and AI features
• Troubleshoot, monitor, and optimize data pipelines and workflows ensuring SLAs are met

• Bachelor’s degree in Computer Science or a related field
• 5+ years of experience in data engineering, data automation, or related discipline
• Ability to design, develop, test, and troubleshoot Python- and SQL-based data pipelines in AWS environments, including Azure integrations
• Strong hands-on experience with Apache Spark and streaming/integration technologies such as Kafka or Flume
• Experience with AWS data and integration services including S3, Glue, Lambda, EMR, and database services
• Practical experience with LLM platforms or models such as Amazon Bedrock, Azure OpenAI, or open-source models in Python workflows
• Experience integrating REST APIs and external services into data pipelines
• Proficiency with source-control and CI/CD platforms like GitHub, Azure DevOps, or Jenkins
• Strong troubleshooting, performance optimization, and support skills for production data platforms
• U.S. citizenship and ability to obtain Federal Public Trust clearance, * Relevant certifications such as AWS Certified Data Engineer - Associate, AWS Certified Machine Learning - Specialty, Azure AI Engineer Associate, or Databricks Certified Data Engineer
• Familiarity with retrieval-augmented generation pipelines, embeddings, and vector-search technologies such as Solr or OpenSearch
• Experience with multi-cloud data integration (AWS and Azure)
• Operational experience with Generative AI workflows, including monitoring and lifecycle management
• Knowledge of data governance tools and infrastructure-as-code tools like Terraform or CloudFormation
• Experience with compliance frameworks such as FedRAMP, PCI-DSS, or HIPAA

Pay range is not a guarantee of compensation or salary, as final offer amount may vary based on factors including but not limited to experience and geographic location. Talascend also offers a variety of benefits including: health and disability insurance, 401(k), EAP, paid time off, and company-paid holidays. The specific programs and options available to an employee may vary depending on date of hire, plan requirements, schedule type, and client work site mandates.