Data Engineer with Mortgage - Onsite

MSYS Inc.

Dallas, TX, United States

9 days ago

Apply on www.dice.com

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Big Data Cloud Computing Information Systems Databases Continuous Integration Data Architecture Information Engineering Data Governance Data Integration Extract Transform Load (ETL) Data Security Data Systems

+16 more

Data Warehousing Database Queries Github Python (Programming Language) PostgreSQL Role-Based Access Control Software Tools Unstructured Data Google Cloud Snowflake Pyspark Information Technology Data Analytics Real Time Data Apache Kafka Legacy Systems

Job description

Design and implement scalable solutions for ever-increasing data volumes, using big data/cloud technologies like Pyspark, Kafka, etc.
Collaborate with cross-functional teams to understand data requirements and provide effective solutions.
Implement real-time data ingestion and processing solutions.
Develop and maintain ETL/ELT processes to support data analytics and reporting.
Implement best practices for data security, integrity, and quality.
Develop data integration and migration strategies to move data from legacy systems to cloud.
Monitor and troubleshoot the performance and availability of the data systems and implement strategies to improve their reliability and scalability.
Manage security and access controls for the data systems, including managing roles and permissions, implementing encryption, and complying with regulatory requirements.

Requirements

Bachelor’s in Engineering or Master’s degree in Computer Science, Information Systems or related field.
Minimum of 5 - 9 years of experience in data engineering.
Experience with databases and data warehouse implementations (Preferred - Snowflake, PostgreSQL).
Strong SQL skills with experience in writing and optimizing complex queries.
Working knowledge of data warehousing, data governance, data quality and data architecture.
Experience in data modelling.
Ability to handle large scale structured and unstructured data from internal and third-party sources.
Hands on experience in Python, Pyspark, Kafka.
Experience with data engineering tools/technologies in Google Cloud Platform cloud environment.
Proficiency in designing and maintaining scalable data architectures.
Experience with CI/CD tools like GitHub.