Data Lead R1012519

Industry Group: Automotive. (Experience in Supply Chain /MFG is a huge plus)

Job Title : Data Lead - R1012519

Location : Plano TX (Local to Dallas area in client office 3days/wk.)
Duration : 12 Months Contract (Potential for extension)

Pay Rate : $85 - $90

Custom Skill Requirements:

• Data Lead
• AWS: Redshift S3 Glue Lambda Kinesis EMR
• Databricks
• Solution Design & Architecture
• Scala
• Python
• SQL

Qualifying Questions:

1. Do you have strong solution design experience a deep understanding of cloud-based data architectures and a proven track record in managing cross-functional teams and projects
2. Do you have Supply Chain & Manufacturing experience
3. Are you certified in: AWS Certified Solutions Architect AWS Certified Big Data Databricks Certified Data Engineer or similar certifications
4. Do you have experience with business intelligence tools (e.g. Tableau Power BI Looker)

Job Description:

We are seeking a Data Lead with expertise in AWS and Databricks to lead the design development and implementation of data solutions. This role requires a hands-on leader who can bridge the gap between technical teams and business stakeholders. The ideal candidate will have strong solution design experience a deep understanding of cloud-based data architectures and a proven track record in managing cross-functional teams and projects.

As a Data Lead you will work closely with senior leadership data engineers data scientists and business stakeholders to create scalable and efficient data solutions that drive business insights decision-making and innovation.

Key Responsibilities:

1. Solution Design & Architecture Design develop and implement end-to-end data solutions on AWS Databricks Snowflake platforms.

• Lead the architecture and implementation of data pipelines ETL processes and real-time data streams.
• Ensure scalable reliable and cost-effective data architectures leveraging cloud-native technologies.
• Collaborate with data engineers and analysts to define data models storage strategies and integration patterns.
• Optimize performance and cost of cloud-based data systems while maintaining data quality and governance.

1. Stakeholder Management

• Engage with business stakeholders to understand their data needs and translate them into technical requirements and solutions.
• Present technical findings and data insights to non-technical business leaders in a clear and actionable way.
• Drive strategic discussions on data governance security and compliance with business leaders.
• Act as the primary point of contact for all data-related initiatives across departments.

1. Team Leadership & Collaboration

• Lead and mentor a team of data engineers and data scientists ensuring high performance and professional development.
• Facilitate communication between business teams and technical teams to ensure alignment on project goals and timelines.
• Promote best practices in data engineering cloud solutions and software development methodologies.
• Manage resource allocation and project delivery to meet deadlines and quality standards.

1. Data Governance & Security

• Oversee the implementation of data governance frameworks ensuring data privacy compliance and security standards are met.
• Work with compliance and legal teams to ensure adherence to regulatory requirements such as GDPR HIPAA and others.
• Implement and monitor best practices in data security including encryption access controls and auditing.

1. Continuous Improvement & Innovation

• Stay updated with the latest trends technologies and best practices in the data and cloud domains particularly in AWS and Databricks.
• Identify opportunities for automation optimization and innovation to improve data operations and increase business value.
• Proactively recommend new technologies and methodologies to enhance the data ecosystem and business capabilities.

Required Skills & Experience:

Technical Skills:

• AWS Services: Proficiency in AWS data services such as Redshift S3 Glue Lambda Kinesis and EMR.
• Databricks: Hands-on experience with Databricks Spark-based data processing and the Databricks Unified Analytics Platform.
• Data Engineering: Expertise in building and managing large-scale data pipelines ETL processes and data integrations.
• Cloud Data Architecture: Strong knowledge of cloud-based data architectures data lakes and data warehouses.
• Programming: Experience in Python Scala SQL and other relevant programming languages.
• Data Modeling: Expertise in designing and implementing relational and non-relational data models.
• Data Governance: Understanding of data governance data privacy and compliance best practices (GDPR HIPAA etc.).
• CI/CD: Familiarity with continuous integration and continuous delivery pipelines for data solutions.

Preferred Qualifications:

• Certifications: AWS Certified Solutions Architect AWS Certified Big Data Databricks Certified Data Engineer or similar certifications.
• Experience with BI Tools: Experience with business intelligence tools (e.g. Tableau Power BI Looker).
• Industry Experience: Experience in Supply Chain /MFG is a plus.

Business & Leadership Skills:

• Stakeholder Management: Proven experience in engaging with senior business stakeholders translating business needs into data solutions and managing expectations.
• Team Leadership: Ability to lead mentor and inspire technical teams fostering a collaborative and high-performance environment.
• Communication: Strong verbal and written communication skills with the ability to explain complex technical concepts to non-technical audiences.
• Project Management: Experience managing multiple data projects simultaneously with an understanding of agile methodologies and project delivery best practices.
• Problem-Solving: Strong analytical and problem-solving skills with the ability to troubleshoot and optimize data systems.