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 Detail-focused Data Analyst with knowledge in data warehousing, process validation and business needs analysis. Proven to understand customer requirements and translate into actionable project plans. Dedicated and hard-working with passion for Big Data. Detail-oriented team player with strong organizational skills. Ability to handle multiple projects simultaneously with a high degree of accuracy. 

Achieved 100% data accuracy in high-volume retail systems through meticulous data management and validation. Optimized workflows and data processes using SQL, advanced Excel, Power BI, Tableau, and Python. Delivered effective cross-functional coordination and documentation through the use of Jira and Confluence.

· Analytical and process-oriented Data Engineer with 3 years of experience in building scalable data solutions and real-time analytics pipelines, with expertise in Azure Data Services, Kafka, Spark, PySpark, SQL, and Power BI, leveraging Agile and Waterfall methodologies to deliver actionable insights.
· Built and orchestrated containerized data infrastructure using Docker Compose with services like Zookeeper, Kafka, Spark (Master/Workers), and Cassandra, enabling efficient development, testing, and streaming of event-driven data pipelines.
· Developed streaming data pipelines using Apache Kafka and Azure Event Hubs, integrating with Spark Structured Streaming and Azure Func tions to process and transform high-throughput event data in real-time for downstream analytics and storage.
· Engineered scalable ETL workflows on Azure Databricks using PySpark and SQL, performing large-scale batch and streaming transformations on structured and semi-structured data, and storing results in Azure Synapse and Data Lake Storage.
· Delivered real-time dashboards in Power BI by integrating with Microsoft Fabric and streaming sources like Kafka and Event Hubs, allowing business stakeholders to monitor operational metrics with minimal latency and drive timely decision-making.
· Worked through the entire data science lifecycle by performing exploratory data analysis (EDA), feature engineering, and dimensionality reduction using PCA, and then training and evaluating machine learning models using Apache Spark MLlib, effectively bridging data engineering with model deployment in distributed environments.

 Experienced in sales and marketing and now making the exciting jump into data and marketing analytics! Over the past three years, I've learned how powerful data can be when it comes to understanding customers, tracking campaigns, and making smart business decisions. That hands-on experience inspired me to dive deeper—so I completed the Google Data Analytics Certificate and built strong skills in SQL, Python, spreadsheets, Tableau, and Looker Studio.  Now, I'm looking for an internship or entry-level opportunity where I can bring my business background, growing analytics toolkit, and genuine love for problem-solving to a team I can grow with. I'm passionate about the work, excited to keep learning, and ready to bring positive energy, creativity, and results wherever I go.   

Nathan Considine

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Grounds Crew Member

Warehouse Associate

Production Associate

Shift Leader/Crew Trainer

Bachelor’s degree - Advanced Marketing Analytics

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