Enterprise Data Strategist

This is a remote opportunity to lead the design, development, and maintenance of an enterprise data platform.

The ideal candidate will collaborate with data engineers, BI engineers, and data business analysts across various platform layers, ensuring a scalable, secure, and high-performance data infrastructure. This role requires a deep understanding of cloud-based big data ecosystems (AWS & Azure), real-time data processing, and enterprise data governance.

Key responsibilities include leading the roadmap and enhancements for the enterprise Big Data Platform, architecting end-to-end data solutions that fulfill business intelligence and analytics needs while ensuring best practices in security, compliance, and operational efficiency.

Additional responsibilities include leading and mentoring a team of data engineers, BI engineers, and cloud architects to implement high-quality, production-ready solutions. The successful candidate will also design and implement modern data architectures, including data lakes, data warehouses, and real-time streaming solutions, leveraging both AWS and Azure technologies.

Other key tasks involve building and optimizing scalable, near real-time data ingestion pipelines, ensuring low-latency, high-throughput data processing for analytics and operational reporting. Additionally, the candidate will architect and manage data streaming solutions using technologies such as Kafka, Kinesis, Apache Flink, or Spark Streaming, ensuring fault tolerance, consistency, and efficiency in real-time workflows.

Familiarity with data security, governance, and compliance across all platforms, integrating IAM, encryption, access control, and data lineage tracking is also required.

Moreover, the candidate will collaborate with stakeholders to define and implement data integration strategies, including ETL, API-based data exchange, and event-driven architectures. Lastly, driving automation and DevOps best practices for data pipeline deployment and monitoring, using tools such as Terraform, CloudFormation, and CI/CD pipelines will be essential.

1. 10+ years of experience in enterprise data architecture, integration, and analytics, with a strong track record in big data solutions.
2. Experience in leading and mentoring teams of data engineers and BI developers.
3. Bachelor's/Master's degree in Computer Science, Data Engineering, or a relevant field from an accredited institution.
4. Strong hands-on experience with:

• Big Data and Cloud Solutions on AWS & Azure, including data lakes, data warehouses, and scalable analytics platforms.
• Data modeling (relational, dimensional, NoSQL) and best practices for high-performance data systems.
• Enterprise data integration (ETL, messaging, streaming, APIs) with tools like Apache NiFi, AWS Glue, Azure Data Factory, Airflow, or Informatica.
• Data pipeline orchestration and event-driven architectures using Apache Spark, AWS Lambda, Azure Functions, Kinesis, or Kafka.
• Cloud security & governance frameworks (IAM, RBAC, encryption, GDPR, HIPAA, SOC2).
• BI & Analytics Tools: Power BI, AWS QuickSight, Tableau.
• Machine Learning & AI: Awareness of AI/ML principles and integration into data pipelines is a plus.

1. Microsoft Certified: Azure Solutions Architect Expert
2. AWS Certified Data Analytics – Specialty

1. Experience with graph databases, data mesh architecture, and knowledge graphs.
2. Hands-on experience with containerized & serverless architectures (Docker, Kubernetes, AWS Fargate).
3. Experience working with real-time anomaly detection and predictive analytics.

1. Mid-Senior level

1. Full-time

1. Information Technology

1. IT Services and IT Consulting