Overview
On Site
$60,000 - $80,000
Full Time
Skills
SQL
Snowflake
Data Warehousing & Cloud Architecture
AWS & Azure
Java & Java Script
ETL/ELT
Data Pipelines & Data Quality
Data Analysis
Data Governance & Security
Hadoop & Spark
DevOps
Data Science
Linux/Unix
QA
CI/CD
Git
Job Details
Core Technical Skills:
- SQL:Proficient in writing, optimizing, and troubleshooting SQL queries for data extraction, transformation, and loading (ETL/ELT).
- Data Warehousing and Cloud Architecture:Understanding of data warehousing concepts, data modeling, metadata management, and cloud-based technologies like AWS or Azure.
- Programming Languages:Familiarity with Python and potentially other languages like Java or JavaScript for scripting and automating data processing tasks.
- Snowflake Specifics:Knowledge of Snowflake's architecture, features (e.g., multi-cluster, data sharing), and performance optimization techniques.
- ETL/ELT Tools:Experience with various ETL/ELT tools and cloud-driven skills for data ingestion and transformation.
- Data Pipelines:Ability to design, build, and maintain end-to-end data pipelines, including data ingestion, transformation, and processing.
- Data Quality and Issue Resolution:Skills in identifying, resolving, and preventing data quality issues, ensuring data integrity and reliability.
Other Important Skills:
- Problem-Solving and Root Cause Analysis:Ability to identify and resolve issues in data pipelines, including performance bottlenecks and data quality problems.
- Business Acumen:Understanding of business needs and how data can be used to drive decision-making.
- Cloud Data Storage and Management:Familiarity with various cloud storage options and their respective strengths and weaknesses.
- Data Analysis:Ability to perform basic data analysis and generate reports or visualizations.
- Data Governance and Security:Understanding of data governance principles and security best practices.
- Communication and Collaboration:Ability to effectively communicate technical information to both technical and non-technical audiences.
- Creativity and Critical Thinking:Ability to think outside the box and find innovative solutions to data engineering challenges.
Optional but Beneficial Skills:
- Hadoop and Spark:Understanding of these big data technologies can be valuable for certain roles.
- DevOps:Knowledge of DevOps principles and tools, such as Git and CI/CD pipelines, for automating data engineering processes.
- Data Science:A basic understanding of machine learning principles can be helpful for certain data engineering roles.
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.