Supervisor, Data

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**Data and Analytics Supervisor (AWS)**

**Responsibilities**:

- Collaborate with cross-functional teams, including data scientists, analysts, engineers, and stakeholders, to understand business requirements and translate them into technical solutions.
- Lead the design and implementation of data engineering solutions in the AWS cloud environment, leveraging services such as Amazon Redshift, Amazon S3, AWS Glue, AWS Lambda, and Kinesis.
- Execute solution delivery engagements, discerning, defining, refining, and documenting client requirements.
- Design and develop scalable and efficient data pipelines to ingest, transform, and load data from multiple sources into data lakes and data warehouses.
- Implement data security and encryption mechanisms to protect sensitive data stored in AWS environments.
- Optimize data storage and retrieval performance, monitor system health and performance metrics, and troubleshoot issues to ensure the reliability and performance of data engineering solutions.
- Lead and mentor a team of data engineers and analysts, providing technical guidance, coaching, and professional development opportunities.
- Stay current on emerging trends, technologies, and best practices in cloud computing, data management, and data engineering, and assess their potential impact on the organization.
- Collaborate with the sales and business development teams to identify customer needs, develop solution proposals, and present technical demonstrations and presentations to prospective clients.

**Required Qualifications**:

- Bachelor’s degree or higher in Computer Science, Information Technology, Business Administration, Engineering, or a related field.
- Minimum of 5 years of related work experience in data engineering and data management, with at least 3 years of experience specifically in AWS technologies.
- Proficiency with AWS services such as Amazon Redshift, Amazon S3, AWS Glue, AWS Lambda, and Kinesis, and excellent grasp of AWS well architected guidelines.
- Experience with data modeling (normalized and de-normalized data models), ETL processes, and designing and implementing data solutions.
- Proficiency with SQL, Python, or other programming languages used for data transformation, analysis, and automation.
- Strong understanding of data architecture principles and data security best practices.
- Excellent communication, presentation, and interpersonal skills, with the ability to articulate technical concepts to both technical and non-technical audiences.
- Ability to interact effectively with internal and external resources at all organizational levels.
- Strong critical thinking and problem-solving skills.
- Must be a team player; able to work in virtual teams and independently.
- AWS certifications such as AWS Data Engineer, AWS Database, or AWS Certified Data Analytics (at least one).

**Preferred Qualifications**:

- AWS Certified Solutions Architect Associate or Professional.
- Experience with Lambda and Kappa architecture frameworks and working with both streaming and batch processing.
- Experience with Quicksight, Power BI, or other reporting and data visualization tools.
- Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools.
- Advanced data and cloud certifications are a plus.