Overview
On Site
Full Time
Skills
Data Flow
Process Improvement
Scalability
Extraction
Customer Acquisition
Operational Efficiency
Performance Metrics
Analytics
Microsoft SSIS
ELT
Documentation
Computer Science
Statistics
Informatics
Information Systems
Training
Transact-SQL
Data Migration
SQL
NoSQL
Database
Object-Oriented Programming
Scripting
Python
Root Cause Analysis
Analytical Skill
Data Structure
Meta-data Management
Management
Machine Learning (ML)
Cloud Computing
Google Cloud
Google Cloud Platform
Amazon Web Services
Snow Flake Schema
Microsoft Azure
GRID
Apache Kafka
Extract
Transform
Load
Workflow Management
Job Details
Data Engineer III
The Data Engineer will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. This role is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. This position will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be comfortable supporting the data needs of multiple teams and systems. Overall, they must strive for efficiency by aligning data systems with business goals.
Duties and responsibilities
Requirements and Qualifications
The Data Engineer will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. This role is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. This position will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be comfortable supporting the data needs of multiple teams and systems. Overall, they must strive for efficiency by aligning data systems with business goals.
Duties and responsibilities
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional/ non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and various cloud technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Work with the business to assist with data-related technical issues and support their data infrastructure needs.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Create complex SQL queries and database objects (stored procs, views, etc.) to pull and manage data.
- Developing complex data pipelines using SSIS packages, Azure Data Factory, or other related ETL/ELT tools to move and translate data
- Create and maintain documentation on data pipelines
Requirements and Qualifications
- Bachelor's degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field; or equivalent combination of education experience and training that provides the required knowledge and skills.
- 4 - 6 years of experience in a Data Engineer role
- Advanced working knowledge of SQL and T-SQL programming
- Experience with ETL and Data Migration
- Experience with relational SQL and NoSQL databases
- Experience with object-oriented/object function scripting languages: Python etc.
- Experience building and optimizing data pipelines, architectures, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
- Experience with Machine Learning is a great plus
- Experience with Cloud technology is a must, preferably Azure Service. Google Cloud Platform or AWS will be considered.
- Experience with Snowflake is a great plus
- Experience with message queuing and stream processing such as Pub-Sub, Azure Event Grid, Kafka etc.
- Experience with data pipeline and workflow management tools such as Airflow, etc.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.