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Company Overview
A leading provider of risk modeling and analytics solutions for the insurance industry is seeking a Data Architect to design and implement cloud-native data platforms and enterprise analytics solutions. The organization supports clients with advanced data products, dashboards, and reporting tools, leveraging AWS cloud technologies and modern data engineering practices to deliver scalable, secure, and high-performance analytics solutions.
Responsibilities
Lead the architecture, design, and implementation of cloud-native data platforms, including ingestion, storage, processing, metadata management, governance, and analytics enablement
Define and maintain data architecture standards for data lakes, lakehouses, data warehouses, data marts, and scalable analytics solutions on AWS
Collaborate with product management, business stakeholders, and cross-functional teams to translate business requirements into data products and analytics solutions
Drive domain-driven data modeling, including canonical data models, dimensional models, and entity relationships aligned to business domains
Design and implement scalable data pipelines (batch and streaming) using AWS services and big-data frameworks (e.g., Spark, EMR, Glue, Athena, Step Functions)
Architect S3-based Data Lake/Lakehouse solutions with open formats like Parquet, Iceberg, or Delta
Build and govern enterprise analytics ecosystems, including semantic layer design, KPI definitions, and reusable curated datasets for BI and downstream consumers
Design and optimize data warehouses and analytical query platforms using Amazon Redshift (RA3/Serverless), Athena, and federated query patterns
Ensure data quality, lineage, observability, and monitoring using CloudWatch, Dynatrace, pipeline metrics, and automated validation checks
Implement security best practices including IAM, encryption (KMS), row/column-level security, PII handling, data masking, and regulatory compliance controls
Architect event-driven and near-real-time analytics solutions using Kafka/MSK, Kinesis, SQS/SNS, and streaming frameworks
Conduct proof-of-concept initiatives to evaluate emerging AWS services and tools for performance, cost, and productivity gains
Mentor engineering and analytics teams on architecture best practices, query performance optimization, modeling standards, and scalability patterns
Qualifications
Bachelor’s degree in Computer Science, Software Engineering, Mathematics, or related field; Master’s preferred
8+ years of experience in data engineering/analytics/platform engineering, including 3+ years in a Data Architect or AWS Data Architecture leadership role
Proven experience designing and implementing AWS-native analytics platforms, data lakes/lakehouse, and enterprise-scale BI/analytics architectures
Hands-on expertise with AWS data services including S3, Glue, Athena, Redshift, EMR, Lake Formation, RDS/Aurora, and orchestration tools like Step Functions, Airflow, or MWAA
Experience with big data processing using Spark/PySpark, partitioning, compaction, incremental processing, and CDC patterns
Deep proficiency in SQL, performance tuning, and scalable design for analytical workloads
Strong understanding of data modeling, metadata/catalog strategies, and data governance concepts
Familiarity with multi-tenant architectures and secure data isolation strategies for analytics workloads
Experience with Agile/Scrum methodologies and cross-team collaboration
Knowledge of infrastructure-as-code tools such as Terraform, CloudFormation, or CDK
Strong communication skills with the ability to influence stakeholders and drive architecture decisions
Preferred Skills
Expertise in S3-based Data Lakes / Lakehouse architectures and open table formats (Apache Iceberg / Delta Lake / Hudi)
Advanced experience with Amazon Redshift (RA3 / Serverless), including performance tuning, workload management, Spectrum, and cost optimization
Proven ability to design and implement data pipelines using AWS Glue, EMR/Spark, Athena, Step Functions for batch and event-driven ingestion
Experience integrating RDS/Aurora (PostgreSQL/MySQL) into analytics ecosystems, including replication/CDC and OLTP-to-analytics workflows
Familiarity with BI platforms such as Power BI, Tableau, QuickSight, Looker, and semantic modeling approaches
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.
1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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