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Lead Data Engineer/Analyst - Contract
Posted about 1 month agoViewed
💎 Seniority level: Lead, 7+ years
🏢 Company: Tech Holding👥 101-250ConsultingFinanceInformation Technology
⏳ Experience: 7+ years
Requirements:
- 7+ years of experience in data engineering, focusing on large-scale data pipelines and systems.
- Expertise in SQL for complex data analysis and manipulation.
- Strong programming skills in Python and shell scripting, with experience in Spark for distributed data processing.
- Hands-on experience with ETL tools and cloud platforms like AWS (e.g., S3, SageMaker, EMR).
- Proficiency in working with relational databases and data warehouses (e.g., Snowflake, Redshift).
- Ability to scale data processing and modeling solutions to handle millions of rows efficiently.
- Strong problem-solving skills with the ability to devise innovative solutions.
- Excellent communication and interpersonal skills, capable of working with technical and non-technical teams.
- Proven ability to work independently and manage priorities effectively in a fast-paced environment.
Responsibilities:
- Design, develop, and optimize data pipelines and workflows for seamless data movement and processing.
- Build and maintain scalable data architectures, including data warehouses (e.g., Snowflake, Redshift) and big data platforms (e.g., Databricks, Spark).
- Implement ETL processes and automate data workflows to ensure high performance and reliability.
- Extract, transform, and manipulate datasets using SQL and Python to create features for analytics and machine learning.
- Analyze large datasets to identify trends, insights, and opportunities for improving data systems and business processes.
- Build dashboards and visualizations to communicate data insights and results effectively.
- Develop, train, and deploy machine learning models within data pipelines to enhance predictive capabilities.
- Ensure model scalability and performance when working with large datasets and distributed systems.
- Utilize AWS tools (e.g., SageMaker, EMR) for managing machine learning workflows and data processing.
- Mentor junior team members on technical projects and coding best practices.
- Partner with stakeholders across analytics, product, finance, and marketing teams to deliver end-to-end data solutions.
- Actively participate in peer reviews, architectural discussions, and documentation efforts
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