Senior Data Architect

4 weeks ago

Charlotte, North Carolina, United States Circle K Full time

Job Title: Senior Data Architect

Circle K is seeking a highly skilled Senior Data Architect to lead the design, development, and implementation of data solutions that empower our organization to derive actionable insights from intricate datasets.

Key Responsibilities:

  • Design and implement data loading and aggregation frameworks across broad areas of the organization.
  • Gather and process raw, structured, semi-structured, and unstructured data using batch and real-time data processing frameworks.
  • Implement and optimize data solutions in enterprise data warehouses and big data repositories, focusing primarily on movement to the cloud.
  • Drive new and enhanced capabilities to Enterprise Data Platform partners to meet the needs of product / engineering / business.
  • Leverage strong Python, Spark, SQL programming skills to construct robust pipelines for efficient data processing and analysis.
  • Implement CI/CD pipelines for automating build, test, and deployment processes to accelerate the delivery of data solutions.
  • Implement data modeling techniques to design and optimize data schemas, ensuring data integrity and performance.
  • Drive continuous improvement initiatives to enhance performance, reliability, and scalability of our data infrastructure.
  • Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
  • Implement best practices for data governance, security, and compliance to ensure the integrity and confidentiality of our data assets.
  • Coaching and mentoring junior Data Engineers: Providing guidance, support, and technical expertise to junior members of the data engineering team.

Requirements:

  • Bachelor's or master's degree in computer science, Engineering, or a related field.
  • Proven experience (8+) in a data engineering role, with expertise in designing and building data pipelines, ETL processes, and data warehouses.
  • Strong proficiency in SQL, Python, and Spark programming languages.
  • Strong experience with cloud platforms such as AWS, Azure, or GCP is a must.
  • Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, and distributed computing frameworks.
  • Knowledge of data lake and data warehouse solutions, including Databricks, Snowflake, Amazon Redshift, Google BigQuery, Azure Data Factory, Airflow, etc.
  • Experience in implementing CI/CD pipelines for automating build, test, and deployment processes.
  • Solid understanding of data modeling concepts, data warehousing architectures, and data management best practices.
  • Excellent communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and drive consensus on technical decisions.
  • Relevant certifications (e.g., Azure, Databricks, Snowflake) would be a plus.

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