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Senior Data Solutions Architect

2 months ago

Charlotte, North Carolina, United States Circle K Full time
Job Summary

We are seeking a highly skilled and experienced Technical Lead Data Engineer to spearhead 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 Solutions: Apply advanced knowledge of Data Engineering principles, methodologies, and techniques to design and implement data loading and aggregation frameworks across broad areas of the organization.
  • Data Processing and Integration: Gather and process raw, structured, semi-structured, and unstructured data using batch and real-time data processing frameworks.
  • Enterprise Data Platform: Implement and optimize data solutions in enterprise data warehouses and big data repositories, focusing primarily on movement to the cloud.
  • Collaboration and Leadership: Drive new and enhanced capabilities to Enterprise Data Platform partners to meet the needs of product/engineering/business stakeholders.
  • Technical Expertise: Leverage strong Python, Spark, SQL programming skills to construct robust pipelines for efficient data processing and analysis.
  • CI/CD Pipelines: Implement CI/CD pipelines for automating build, test, and deployment processes to accelerate the delivery of data solutions.
  • Data Modeling and Governance: Implement data modeling techniques to design and optimize data schemas, ensuring data integrity and performance, and drive continuous improvement initiatives to enhance performance, reliability, and scalability of our data infrastructure.
  • Stakeholder Collaboration: Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
  • Data Security and Compliance: Implement best practices for data governance, security, and compliance to ensure the integrity and confidentiality of our data assets.
  • Team Leadership: Coach and mentor junior Data Engineers, providing guidance, support, and technical expertise to junior members of the data engineering team.
Requirements
  • Education: Bachelor's or master's degree in computer science, engineering, or a related field.
  • Experience: Proven experience (8+) in a data engineering role, with expertise in designing and building data pipelines, ETL processes, and data warehouses.
  • Technical Skills: Strong proficiency in SQL, Python, and Spark programming languages, and experience with cloud platforms such as AWS, Azure, or GCP.
  • Big Data Technologies: Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, and distributed computing frameworks.
  • Data Lake and Warehouse Solutions: Knowledge of data lake and data warehouse solutions, including Databricks, Snowflake, Amazon Redshift, Google BigQuery, Azure Data Factory, Airflow, etc.
  • CI/CD Pipelines: Experience in implementing CI/CD pipelines for automating build, test, and deployment processes.
  • Communication and Leadership: Excellent communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and drive consensus on technical decisions.
  • Certifications: Relevant certifications (e.g., Azure, Databricks, Snowflake) would be a plus.