Senior IT Data Engineer

Bryant Technologies, Inc
6 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

Java
Agile Methodologies
Apache HTTP Server
Databases
Continuous Integration
Data Infrastructure
Data Integration
ETL
Data Mining
Database Development
DevOps
Digital Assets
Hadoop
MapReduce
HBase
Hive
Microsoft SQL Server
Performance Tuning
Standard Sql
Cloudera
Data Processing
GIT
Pandas
PySpark
Kafka
Data Pipelines

Job description

This role involves participating in the planning and execution of policies, practices, and projects designed to acquire, control, protect, and enhance the value of organisational data assets., Included but not limited to:Data Acquisition: Facilitate obtaining data from variety of sources in correct formats while adhering to quality standards.Pipeline Development: Build robust data pipelines that clean, transform, and aggregate unorganized data into databases.Platform Operations: Develop, maintain, monitor, and manage the long-term operations of data pipelines or processing systems within the Cloudera Data Platform.Issue Resolution: Resolve information flow and content issues as they arise.CI/CD Implementation: Implement and maintain continuous integration and continuous delivery (CI/CD) pipelines and manage data platforms.Strategic Planning: Participate in the planning of practices and projects to enhance data asset value

Requirements

General Experience: 5+ years of experience in application/data development, specifically with Python.Specialized Experience: 5+ years of experience with data integration and ingestion tools, such as Apache NiFi.Methodology: Experience working with Scrum and Kanban methodologies.Platform Experience: Proficiency in the long-term operations of data pipelines or processing systems running in the Cloudera Data Platform.**ship is a requirement for this position, Data Processing & Engineering: Proficiency in PySpark, pandas, or dbt.Data Ingestion: Expertise in Apache NiFi.Languages & Databases: Advanced knowledge of SQL, Java, and Microsoft SQL Server.Distributed Computing: Experience with platforms including Hadoop, MapReduce, Hive, HBase, Kafka, and Spark.DevOps & Tools: Understanding of git and DevOps-enabled technologies.Systems: Proficiency in UNIX/Linux, including basic commands and shell scripting.Technical Operations: Knowledge of data extraction, transformation, loading (ETL), and performance tuning.

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