Data Engineer
4 weeks ago
**Responsibilities**
- Build and maintain the Data Warehouse (DW) to store both structured and non
- structured data; and make it optimized for reading, aggregating, and querying large volumes of data.
- Create and maintain optimal data pipeline architecture.
- Build the data pipeline infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Develop different components of the data management framework, including the Data Definitions for all data and the Metadata for data transformation/processing description.
- Assemble large, complex data sets that meet functional/non-functional business requirements.
- Work with stakeholders including the Executive, Product and Data Science teams to assist with data-related technical issues and support their data infrastructure needs.
- Prepare data for prescriptive and predictive modeling by the Data Science team to build and optimize our products and services.
- Create data tools for data analysts that assist them in build reports, dashboards and extract useful business insights.
- Assist in building analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Keep our data separated and secure through multiple data centers.
- Work closely with quality assurance team to enhance data quality and reliability.
- Keep up to date with latest trends and technologies in data engineering and processing field.
**Requirements**:
- A minimum of 4-6 years of work experience in a similar role
- Strong project management and organizational skills.
- Bachelor’s degree in Computer Science/Engineering or any other relevant field.
- Advanced working SQL knowledge and experience working with relational and NoSQL databases.
- Experience in building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift, etc.
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- A successful history of manipulating, processing and extracting value from large-disconnected datasets.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Strong analytical and problem-solving skills.
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