Job description

We have many opportunities available on our other career site pages. Click here to link to our careers page! Signet Jewelers is the world s largest retailer of diamond jewelry, operating more than 2,800 stores worldwide under the iconic brands: Kay Jewelers, Zales, Jared, H.Samuel, Ernest Jones, Peoples, Banter by Piercing Pagoda, Rocksbox, JamesAllen.com and Diamonds Direct. We are a people-first company and t his core value is at the heart of everything we do, from empowering our valued team members, to collaborating with our customers, to fostering the communities in which we live and serve. People – and the love their actions inspire – are what drive us. We’re not only proud of the love we inspire outside our walls, we’re especially proud of the diversity, inclusion and equity we’re inspiring inside. There are dynamic career paths awaiting you – rewarding opportunities to impact the lives of others and inspire love. Join us! Senior Technical Lead Remote POSITION SUMMARY : We are seeking a Sr Technical Lead, Data Engineering to provide hands on technical leadership across enterprise data platform initiatives. This role combines data architecture, solution design and engineering leadership to deliver scalable, secure, reliable and governed data solutions on AWS. The ideal candidate will lead technical design and implementation, define reusable data and integration patterns, and guide engineering teams through development, code reviews, testing, deployment and optimization. The role will work closely with platform architects, engineers, analytics teams and business stakeholders to ensure solutions align with enterprise architecture and engineering standards. RESPONSIBILITIES: Provide hands on technical leadership through solution design, code reviews, design walkthroughs, troubleshooting and implementation guidance. Lead technical design and engineering execution across enterprise data initiatives from requirements through production deployment. Translate architecture and business requirements into detailed technical designs, data models and implementation patterns. Design, implement and evolve event driven, API based and real time streaming architectures. Define and enforce engineering best practices for data ingestion, transformation, storage, processing and access across analytical and operational workloads. Design and implement scalable data solutions using AWS native services, with hands on expertise in Python, AWS Glue, Lambda, API Gateway, Kinesis, EventBridge, SQS/SNS, Redshift and RDS. Lead end to end data modeling, including conceptual, logical and physical models for analytical and operational use cases. Own schema design and evolution across structured and semi structured data formats, including relational, JSON and Parquet. Establish reusable batch, CDC, API and streaming integration patterns to accelerate engineering delivery. Embed data quality, metadata, lineage, security and governance requirements into solution design and implementation. Ensure data solutions effectively support analytics, reporting, data products and AI/ML use cases. Ensure pipelines and integrations are fault tolerant, observable, resilient, scalable and performant. Design monitoring, logging and event based alerting using Amazon CloudWatch, SNS and related AWS services. Lead performance tuning and optimization across pipelines, Redshift workloads and data processing solutions. Drive CI/CD, automated testing, deployment practices and engineering quality standards. Identify and address technical debt, automation opportunities and reusable engineering capabilities. Lead troubleshooting and root cause analysis for complex data, integration and production issues. Provide technical mentoring and guidance to data engineers and promote consistent engineering and coding standards. Partner with Platform Architecture to ensure implementations align with enterprise platform architecture, security and technology standards. Collaborate with data engineers, analytics teams, integration partners and business stakeholders to deliver business aligned data solutions. Evaluate and apply AI driven engineering capabilities, including Agentic AI and LLM based approaches for data ingestion, data product development and developer productivity. POSITION QUALIFICATIONS : 10 years of software engineering, data engineering or relevant technology experience, including technical leadership responsibilities. Strong hands-on experience designing and delivering enterprise-scale data platforms on AWS. Deep expertise with AWS services including Glue, Lambda, Redshift, RDS, Kinesis, EventBridge, API Gateway, SQS, SNS and CloudWatch. Strong programming experience with Python and SQL. Strong understanding of modern data architecture patterns, including data lake, lakehouse, data warehouse and data mesh. Strong experience with data modeling and designing scalable data structures for analytical and operational workloads. Strong understanding of event driven architectures, real time streaming, CDC and API based integration patterns. Experience with Databricks, including Delta Lake, Unity Catalog, Databricks workflows and integration with AWS services Experience implementing governance, lineage and data quality capabilities within Databricks is preferred. Experience designing solutions supporting analytics, reporting, AI/ML and data product consumption. Experience implementing data quality, metadata, lineage and governance within enterprise data platforms. Working knowledge of AWS networking, IAM, security and access control patterns. Experience with Infrastructure as Code, preferably Terraform or AWS CDK. Strong understanding of Git, CI/CD, DevOps and automated deployment practices. Experience with Agentic AI or AI driven data engineering, including LLM assisted ingestion, engineering automation or data product creation is preferred. Demonstrated ability to perform technical design and code reviews, mentor engineers and drive engineering best practices. Strong problem solving skills with the ability to troubleshoot complex distributed data and integration solutions. Excellent communication skills with the ability to work effectively with architects, engineers, business stakeholders and technology partners. BENEFITS & PERKS: Competitive healthcare, dental & vision insurance 401(k) matching after one year of employment Generous time off company holidays Merchandise discount Learning & Development programs Much more! The salary range for this opportunity is 132,000-150,000. Base pay offered may vary depending on geographic region, internal equity, job related knowledge, skills and experience, among other factors. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Requirements

Must-haves

We have many opportunities available on our other career site pages. Click here to link to our careers page!
Senior Technical Lead
Provide hands on technical leadership through solution design, code reviews, design walkthroughs, troubleshooting and implementation guidance.
Lead technical design and engineering execution across enterprise data initiatives from requirements through production deployment.
Translate architecture and business requirements into detailed technical designs, data models and implementation patterns.
Design, implement and evolve event driven, API based and real time streaming architectures.
Define and enforce engineering best practices for data ingestion, transformation, storage, processing and access across analytical and operational workloads.
Design and implement scalable data solutions using AWS native services, with hands on expertise in Python, AWS Glue, Lambda, API Gateway, Kinesis, EventBridge, SQS/SNS, Redshift and RDS.
Lead end to end data modeling, including conceptual, logical and physical models for analytical and operational use cases.
Own schema design and evolution across structured and semi structured data formats, including relational, JSON and Parquet.
Establish reusable batch, CDC, API and streaming integration patterns to accelerate engineering delivery.
Embed data quality, metadata, lineage, security and governance requirements into solution design and implementation.
Ensure data solutions effectively support analytics, reporting, data products and AI/ML use cases.
Ensure pipelines and integrations are fault tolerant, observable, resilient, scalable and performant.
Design monitoring, logging and event based alerting using Amazon CloudWatch, SNS and related AWS services.
Lead performance tuning and optimization across pipelines, Redshift workloads and data processing solutions.
Drive CI/CD, automated testing, deployment practices and engineering quality standards.
Identify and address technical debt, automation opportunities and reusable engineering capabilities.
Lead troubleshooting and root cause analysis for complex data, integration and production issues.
Provide technical mentoring and guidance to data engineers and promote consistent engineering and coding standards.
Partner with Platform Architecture to ensure implementations align with enterprise platform architecture, security and technology standards.
Collaborate with data engineers, analytics teams, integration partners and business stakeholders to deliver business aligned data solutions.

Nice-to-haves

Experience implementing governance, lineage and data quality capabilities within Databricks is preferred.
Experience with Agentic AI or AI driven data engineering, including LLM assisted ingestion, engineering automation or data product creation is preferred.

Application prep

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Keywords to mirror

awsapipythonaimlci/cdllmsql

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)