DATA ENGINEER

Digipulse Technologies, Inc.; Cherry Hill Township, Northern (NJ, KY); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Digipulse Technologies, Inc. is seeking a data engineering specialist to design, develop, and maintain scalable data pipelines and ETL processes for the company's data infrastructure.

The role involves collaborating with stakeholders, modeling data for analytics, ensuring data quality, and documenting best practices. Relocation/telecommuting may be required with travel to client locations in the United States.

Qualifications

• Design, develop and maintain scalable data pipelines and data sets.
• Collaborate with stakeholders to understand data requirements and deliver ETL processes.
• Ensure data integrity, quality and performance across systems.

Responsibilities

• Develop ETL processes to transform raw data for analysis.
• Design data models to support analytics and reporting needs.
• Document pipelines and best practices for knowledge sharing.
• Identify and resolve data quality and performance issues.
• Work with business analysts and software engineers to meet data needs.
• Travel to client locations within the United States for assignments.

Education

Master’s degree in computer science or related field

Bachelor’s degree with 5+ years of experience in related fields

Tools

SQL

SAS

Python

Hive

Tableau

GitHub

Jira

MySQL

Oracle

PL/SQL

MongoDB

Informatica ETL

AWS

Databricks

Azure Data Factory

Apache-Airflow

Flask

Docker

Kubernetes

Jenkins

Splunk

Snowflake

Google Analytics

Job description

Critical role in designing, developing and maintaining scalable data pipelines, data sets, and systems for the company’s data infrastructure. Will be collaborating with stakeholders to understand data requirements; Develop ETL (Extract, Transform, Load) processes to change raw data into usable formats for analysis, use and cost effectiveness utilizing techniques such as partitioning, indexing, and caching; Design and implement data models to support the business analytical and reporting needs; ensure data integrity, consistency, and performance and identify errors and performance issues; perform data quality checks for accuracy and consistency of data across systems and platforms; Work closely with business analysts/software engineers to understand their data needs and provide technical expertise and support. Document data pipelines, processes, and best practices for knowledge sharing and future reference; Identify and resolve issues to ensure uninterrupted data flow and availability. Relocation/ telecommuting may be required plus travel to various unanticipated client locations within the United States for short- and long-term assignments.

LANGUAGES, SKILLS AND TOOLS

• SQL
• SAS
• Python
• PyCharm
• Hive
• Tableau
• GitHub
• Jira
• MySQL
• Oracle
• PL/SQL
• MongoDB
• Informatica ETL
• AWS
• Databricks
• Azure Data Factory
• Apache-Airflow
• Flask
• Docker
• Kubernetes
• Jenkins
• Splunk
• Snowflake
• SAS
• Google Analytics
• Supervised and Unsupervised Machine Learning Algorithms
• K-Means
• SVM
• Statistics
• KNN
• Time Series Forecasting
• Survival Analysis
• ETL
• Business Intelligence
• Text Mining
• Clustering
• Cross-Validation
• Support Vector Machine
• Decision Tree
• Random Forest
• A/B Testing
• Market Basket Analysis
• Linear Discriminant Analysis
• Gradient Boosting
• Bagging
• Natural Language Processing
• Sentimental Analysis
• Data Modeling
• PCA

EDUCATION

Master’s degree in computer science/computer applications/business Analytics/Technology/Engineering (Mechanical/ I.T./Electrical). Will accept bachelor’s degree in computer science/computer applications/business Analytics/Technology/Engineering (Mechanical/ I.T./Electrical) plus five (5) years of progressive experience in related fields in lieu of master’s degree. Will accept foreign education equivalent.