Sr. Data Engineer/Analyst - Contract

The Role: 

We’re seeking an experienced Senior Data Engineer/Analyst with a strong background in streaming data processing, data science, and large-scale data architectures. The ideal candidate has a proven track record of building scalable data solutions, leveraging real-time data pipelines, and applying machine learning to solve complex business challenges. You’ll work across the full data lifecycle—from ingestion and transformation to modeling, analytics, and insights generation—while collaborating with stakeholders to drive data-driven decisions.

Key Responsibilities:

• Design, develop, and optimize scalable batch and streaming data pipelines using technologies like Apache Kafka, Kinesis, Spark Streaming, and Flink.
• Build and maintain data architectures (e.g., Snowflake, Redshift, Databricks, Spark).
• Implement real-time and batch ETL processes to ensure high performance and reliability.
• Develop machine learning models and integrate them into data pipelines.
• Utilize cloud platforms (AWS preferred, e.g., Kinesis, SageMaker, EMR, Glue) for scalable data processing and analytics.
• Ensure model scalability and performance when working with large datasets.
• Extract, transform, and manipulate large datasets using SQL and Python to generate insights.
• Develop dashboards and visualizations to communicate insights to stakeholders.
• Mentor junior engineers on best practices and emerging technologies.
• Collaborate with cross-functional teams across analytics, product, finance, and marketing to develop end-to-end data solutions.

Required Skills & Experience:

• 7+ years of experience in data engineering, data science, or real-time data processing.
• Expertise in streaming data processing (Kafka, Kinesis, Flink, Spark Streaming, or similar).
• Advanced SQL skills for complex data transformations and analysis.
• Strong programming skills in Python, Scala, or Java, with experience in distributed computing frameworks (Spark, Flink, etc.).
• Hands-on experience with ETL tools and cloud platforms (AWS, GCP, or Azure).
• Proficiency with data warehouses (Snowflake, Redshift, BigQuery).
• Experience building and deploying machine learning models at scale.
• Strong problem-solving and analytical skills, with the ability to optimize large-scale data systems.
• Excellent communication skills and ability to work cross-functionally.

Preferred Qualifications:

• Experience with real-time analytics and event-driven architectures.
• Background in data science, predictive modeling, and AI/ML.
• Familiarity with BI tools (e.g., Tableau, Looker, Power BI).
• Knowledge of subscription-based products and financial analytics.

What we Offer: 

• Remote Work Opportunities
• Flexible Work Hours
• Professional Development Opportunities