For companies:
For professionals:
For everyone:
For developers:
Responsibilities
Overview:
- This role focuses on backend development and integrations for building and maintaining enterprise data warehouses and data lakes.
- The ideal candidate will possess a deep understanding of data architecture, ETL pipelines, and integration technologies, ensuring seamless data flow and accessibility across the organization, with a strong focus on Snowflake, dbt, and Fivetran.
Key Responsibilities:
- Design, develop, and maintain scalable backend systems to support data warehousing and data lake initiatives.
- Build and optimize ETL/ELT processes to extract, transform, and load data from various sources into centralized data repositories.
- Develop and implement integration solutions for seamless data exchange between systems, applications, and platforms.
- Collaborate with data architects, analysts, and other stakeholders to define and implement data models, schemas, and storage solutions.
- Ensure data quality, consistency, and security by implementing best practices and monitoring frameworks.
- Monitor and troubleshoot data pipelines and systems to ensure high availability and performance.
- Stay up-to-date with emerging technologies and trends in data engineering and integration to recommend improvements and innovations.
- Document technical designs, processes, and standards for the team and stakeholders.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field; equivalent experience considered.
- Proven experience as a Data Engineer with 3 or more years of experience; or in a similar backend development role.
- Strong proficiency in programming languages such as Python, Java, or Scala.
- Hands-on experience with ETL/ELT tools and frameworks (e.g., dbt, etc.).
- Extensive knowledge of relational and non-relational databases (e.g., SQL, NoSQL).
- Expertise in building and managing enterprise data warehouses (e.g., Snowflake, Amazon Redshift, Google BigQuery) and data lakes (e.g., AWS S3, Azure Data Lake).
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their data services.
- Experience with API integrations and data exchange protocols (e.g., REST, SOAP, JSON, XML).
- Solid understanding of data governance, security, and compliance standards.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication and collaboration abilities.
Preferred Qualifications:
- Certifications in cloud platforms (AWS Certified Data Analytics, Snowflake, etc.).
- Experience with big data technologies (e.g., Apache Hadoop, Spark, Kafka).
- Knowledge of data visualization tools (e.g., Tableau, Power BI) for supporting downstream analytics.
- Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes, Jenkins).
Closes in:
0
days
0
hours
0
min
0
sec
tune NOT FOR YOU? IMPROVE YOUR RESULTS