Data Engineer/(Python Developer)
Hybrid to the office (NO RELOCATION) Aventura, FL
Overview:
We are seeking an experienced Data Engineer to lead the design, development, and optimization of end-to-end data pipelines and cloud-based solutions. You will be responsible for architecting scalable data and analytic systems, ensuring data integrity, and implementing software engineering best practices and patterns. The ideal candidate has a strong background in ETL, big data technologies, and cloud services, with a proven ability to drive complex projects from concept to production.
Key Responsibilities:
Data Architecture and Engineering
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Design and implement scalable data pipelines for data ingestion, transformation, and storage.
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Architect and optimize data lakes and data warehouses to support analytics and reporting needs.
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Develop robust ETL processes to integrate structured and unstructured data from diverse sources.
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Ensure high data quality through cleaning, validation, and transformation techniques.
Cloud and Big Data Solutions:
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Lead the implementation of big data frameworks such as Hadoop and Spark for processing large datasets.
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Develop and optimize solutions on cloud platforms, including AWS S3, Azure Data Lake, Google BigQuery, and Snowflake.
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Manage data lakes to facilitate efficient data access and processing for downstream applications.
Database and Data Warehousing:
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Design, implement, and manage relational (SQL) and non-relational (NoSQL) database systems.
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Lead database architecture efforts, including schema design, query optimization, and performance tuning.
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Oversee the design and management of data warehouses, ensuring reliability, scalability, and security.
Software Development and Automation:
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Utilize Python and SQL to develop efficient, production-ready code for data pipelines and integrations.
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Implement scripting automation using Bash and PowerShell to streamline workflows.
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Leverage version control (Git) and follow best practices in code optimization, unit testing, and debugging.
Collaboration and Leadership:
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Act as a technical leader, providing guidance on best practices.
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Collaborate with cross-functional teams (Data Scientists, Software Engineers, Analysts) to meet business objectives.
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Drive innovation by evaluating and integrating emerging tools, technologies, and frameworks.
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Establish and maintain CI/CD pipelines to ensure efficient deployment and system reliability.
Required skillset:
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Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
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5+ years of experience as a Data Engineer with expertise in building large-scale data solutions.
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Proficiency in Python, SQL, and scripting languages (Bash, PowerShell).
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Deep understanding of big data tools (Hadoop, Spark) and ETL processes.
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Hands-on experience with cloud platforms (AWS S3, Azure Data Lake, Google BigQuery, Snowflake).
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Strong knowledge of database systems (SQL, NoSQL), database design, and query optimization.
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Experience designing and managing data warehouses for performance and scalability.
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Proficiency in software engineering practices: version control (Git), CI/CD pipelines, and unit testing.
Preferred:
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Strong experience in software architecture, design patterns, and code optimization.
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Expertise in Python-based pipelines and ETL frameworks.
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Experience with Azure Data Services and Databricks.
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Excellent problem-solving, analytical, and communication skills.
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Experience working in agile environments and collaborating with diverse teams.