The role
From Fidelity Investments's own posting.
Job Description:
The role:
Data Engineer with proven expertise in real-time data platforms, Snowflake, AWS, data modelling, and analytics-focused data engineering.
Location: Galway
Ways of Working: in Office
We are seeking a Data Engineer to help build and evolve the analytics platform that powers reporting, workforce planning, forecasting, operational insights, and modernization initiatives across the Fidelity Contact Center ecosystem. The Contact Center platform services over 20M clients and processes more than 35M customer interactions per year while operating on a 24x7 basis.
This role focuses on designing scalable data models, developing cloud-native and event-driven data solutions, and delivering trusted, analytics-ready data products on Snowflake and AWS. The ideal candidate combines strong data modeling expertise with modern software engineering and cloud-native development practices.
The Expertise We’re Looking For
5+ years of experience in Data Engineering, Analytics Engineering, or Data Platform Engineering.
Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or related field.
Strong experience in data modeling , including dimensional modeling and analytical data design.
Expertise in SQL development, query optimization, and performance tuning.
Hands-on experience with Snowflake and modern cloud data platforms.
Expertise with read/write-intensive OLTP databases and/or Operational Data Stores (ODS).
Experience with real-time or near-real-time data platforms, databases, or processing systems would be of benefit.
Experience designing analytics-ready datasets for reporting, forecasting, and business intelligence.
Experience with AWS services and cloud-native architectures.
Knowledge of data warehousing, distributed systems, and modern data architectures.
Experience with Git, CI/CD pipelines, automated testing, and DevOps practices.
Strong analytical, problem-solving, and communication skills.
The Skills You Bring
Data Modeling (Conceptual, Logical, Physical, Dimensional)
Snowflake (Data Sharing, Snowpipe, Streams, Tasks, Dynamic Tables, Security)
SQL and Data Warehousing
AWS (S3, Lambda, SNS, SQS, IAM, Aurora/RDS, ECS/EKS, CloudWatch)
Kafka, Kinesis, or other streaming platforms
REST APIs and integration patterns
CI/CD and Infrastructure-as-Code (Terraform/OpenTofu/CloudFormation)
Monitoring, Alerting, Observability, and Production Support
Data Governance, Metadata Management, Security, and Data Masking
Experience building enterprise analytics platforms on Snowflake and AWS.
Experience with Power BI, Tableau or similar tools.
Experience with Collibra, Alation, or other data governance platforms.
Your Key Responsibilities
Design and implement conceptual, logical, and physical data models that support analytics, reporting, forecasting, and operational decision-making.
Develop and maintain analytics-ready datasets and curated data products in Snowflake.
Build event-driven data pipelines and integrations using AWS and streaming technologies.
Partner with business and technology teams to translate requirements into scalable data solutions.
Implement data quality, monitoring, observability, reconciliation, and resiliency capabilities.
Apply data governance, security, privacy, and access-control best practices.
Automate deployments and operational processes using CI/CD and Infrastructure-as-Code.
Support and continuously improve critical production data platforms.
Knowledge of data warehousing, distributed systems, and modern data architectures.
Experience with Git, CI/CD pipelines, automated testing, and DevOps practices.
Strong analytical, problem-solving, and communication skills.
Success in the Role
The successful candidate will help build the data foundation that powers Contact Center modernization by delivering scalable, governed, and analytics-ready data products that support reporting, workforce planning, forecasting, operational insights, and future AI-driven capabilities.
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Category:
Information Technology