Senior Data Engineer
2 weeks ago
Analytics Data Engineer – Treasury/Finance Duration: 6 months
Location: Remote or Hybrid (must be able to visit the office for technical issues or special occasions)
Data Collection & Preparation: Gather data from multiple sources, clean and preprocess to ensure accuracy and consistency.
Statistical Analysis: Apply statistical modeling techniques (hypothesis testing, regression, clustering) to identify patterns, trends, and relationships.
Programming & Analysis: Use Python, SQL, or R to analyze data and uncover insights that address business challenges such as customer behavior, operational efficiency, and cost optimization.
Create dashboards and visualizations using Tableau, Power BI, or matplotlib to simplify complex data for stakeholders and support data-driven decisions.
Data Engineering & ETL: Develop robust ETL pipelines to handle large datasets from IBM Netezza/Hadoop and other sources, ensuring efficient processing and transformation.
Advanced Analytics: Incorporate predictive modeling and machine learning techniques to solve complex business problems.
Collaboration: Work with business teams to translate requirements into scalable, actionable data solutions.
Programming & Tools
~8-10 years of strong experience in Python, SAS, and SQL
~ Power BI, DAX, and M Code for dashboard development
~ Proficiency in MS 365 Suite: Office, Power Automate, SharePoint, OneDrive
Database & Data Engineering
Advanced SQL Server configuration for high-throughput analytics (memory allocation, parallel query execution)
Deep understanding of SQL Server recovery models, backup/restore strategies, and disaster recovery planning
Design and implementation of ETL pipelines with incremental loads and change data capture
Data staging and processing large-scale datasets efficiently
Data Architecture
Batch processing pipelines using Python and SQL
Knowledge of RDBMS, NoSQL, and data file formats (CSV, Parquet, JSON)
Translate business requirements into scalable, optimized data models
Cloud & Big Data
~ Strong experience with AWS (Redshift, Glue, MLOps)
Previous Data Analyst experience
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