Engineer, Data

Job Description

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.

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 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., Apache Airflow, Talend, Informatica, etc.).

· Extensive knowledge of relational and non-relational databases (e.g., SQL, NoSQL, PostgreSQL, MongoDB).

· 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, Azure Data Engineer, 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).