Define and implement a scalable, enterprise-wide data architecture aligned with business and technology goals.
Develop a data strategy roadmap, ensuring long-term sustainability, scalability, and efficiency.
Partner with executive leadership, product teams, and engineering to ensure data initiatives drive business value.
Establish enterprise data governance, security, and compliance frameworks leveraging tools like Collibra or Alation.
Oversee the design and evolution of data lakes, data warehouses, and cloud-based analytics platforms using Databricks, Snowflake, BigQuery, or Redshift.
Lead the adoption of modern data architecture patterns, including event-driven architectures, real-time data streaming (Kafka, Pulsar), and AI-driven analytics.
Provide guidance on database optimization, indexing, partitioning, and storage strategies for tools like PostgreSQL, MySQL, and NoSQL solutions like MongoDB or Cassandra.
Evaluate emerging technologies, making recommendations for tools and platforms that enhance data capabilities.
Direct ETL/ELT strategies, ensuring seamless data flow across systems with Python, Apache Airflow, dbt, or Informatica.
Architect cloud-based solutions (AWS, Azure, or GCP) using services such as AWS Glue, Azure Synapse, and Google Cloud Dataflow to support analytics, AI, and operational use cases.
Ensure API-first design for data integration using GraphQL, RESTful APIs, or event-driven architectures (Kafka, AWS Kinesis, Pub/Sub).
Define and oversee data quality, lineage, and cataloging efforts using Great Expectations, Monte Carlo, or DataHub.
Develop policies for data privacy, access control, and encryption, ensuring compliance with GDPR, CCPA, HIPAA, or other relevant regulations.
Implement enterprise-wide metadata management and data lineage tracking using Collibra, Alation, or Data Catalog solutions.
Drive best practices for data security and compliance audits, leveraging IAM tools and cloud security solutions.
Lead a team of data architects, engineers, and analysts, mentoring them on best practices.
Act as a liaison between business and technical teams, translating business needs into scalable data solutions.
Champion a culture of innovation, ensuring the data team is adopting cutting-edge methodologies.

Requirements

10+ years of experience in data architecture, data engineering, or related fields.
Bachelor’s degree (Master’s preferred) in Computer Science, Applied Mathematics, Statistics, Machine Learning, or a closely related field (or foreign equivalent).
Proven track record in designing large-scale, enterprise data architectures.
Expertise in SQL, NoSQL, and distributed database technologies such as Snowflake, Databricks, BigQuery, Redshift, PostgreSQL, MongoDB, and Cassandra.
Strong experience with cloud-based data platforms (AWS, Azure, GCP) and services like AWS Glue, Azure Data Factory, and Google Dataflow.
Deep understanding of data modeling, ETL/ELT processes, and data pipeline optimization using dbt, Apache Airflow, Informatica, or Talend.
Experience with real-time streaming technologies (Kafka, Spark Streaming, Apache Flink, AWS Kinesis).
Strong knowledge of data security, governance, and compliance frameworks.
Excellent verbal and written communication skills and ability to resolve disputes effectively and efficiently
Outstanding presentation and public speaking skills
Mastery independent decision making, analysis and problem-solving skills
Ability to quickly understand and assess complex projects, systems and ecosystems and identify relevant relationships and connections between them
Mastery planning and organizational skills and techniques
Communicate effectively with senior management and key stakeholders
Ability to influence, build relationships, understand organizational complexities, manage conflict and navigate politics
Familiarity with the healthcare data domain with previous experience working with healthcare datasets is a plus
Strong Python programming skills, with expertise in data manipulation and pipeline development using Pandas, PySpark, NumPy, and SQLAlchemy.
Experience with AI/ML-driven analytics architectures and MLOps frameworks like MLflow or SageMaker.
Hands-on experience with Infrastructure as Code (Terraform, CloudFormation).
Familiarity with Graph databases and knowledge graphs (Neo4j, Amazon Neptune).
Certifications in cloud data services (AWS Certified Data Analytics, Google Professional Data Engineer, Databricks Certified Data Engineer).

Benefits

Medical, Dental and Vision Coverage
401K Plan with Company Match
PTO
Paid Parental Leave
Income Protection
Work Life Assistance Program
Flexible Spending Accounts
Educational Benefits
Worldwide Scholarship Program
Volunteer Opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata engineeringSQLNoSQLETLELTdata modelingdata pipeline optimizationreal-time data streamingcloud-based data platforms

Soft Skills

communication skillspresentation skillsproblem-solving skillsorganizational skillsrelationship buildinginfluenceconflict managementdecision makingmentoringinnovation

Certifications

AWS Certified Data AnalyticsGoogle Professional Data EngineerDatabricks Certified Data Engineer