Data Engineer Specialist

Job Overview

As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support business intelligence, analytics, and product development. You will manage and optimize databases, integrate data from multiple sources, ensure data quality and reliability, and collaborate with cross-functional teams to deliver secure and efficient data solutions.

Key Responsibilities (Job Description)

1. Design, develop, and maintain scalable ETL/ELT data pipelines.
2. Build and optimize data architecture for data warehousing and analytics.
3. Integrate data from multiple internal and external sources while ensuring data quality and consistency.
4. Develop and maintain relational and non-relational databases.
5. Optimize SQL queries, database performance, and data processing workflows.
6. Implement data validation, monitoring, and quality assurance processes.
7. Collaborate with Data Analysts, Data Scientists, Product, and Engineering teams to support business requirements.
8. Deploy and maintain data pipelines using orchestration and workflow management tools.
9. Manage cloud-based data infrastructure and storage solutions.
10. Ensure data security, governance, backup, and compliance with company policies.
11. Troubleshoot data pipeline issues and continuously improve system performance.
12. Stay updated with emerging technologies and best practices in data engineering.

Qualifications

1. Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
2. 2–4 years of experience as a Data Engineer or a similar role.
3. Proficient in Python, Java, Scala, or other relevant programming languages.
4. Strong experience with SQL and relational databases such as MySQL, PostgreSQL, or SQL Server.
5. Knowledge of NoSQL databases such as MongoDB, Cassandra, or Redis.
6. Experience building ETL/ELT pipelines.
7. Familiar with Big Data technologies.
8. Experience with orchestration and containerization tools such as Docker, Kubernetes, and Apache Airflow.
9. Experience working with Google Cloud Platform (GCP) services.
10. Good understanding of business processes and how data supports business decisions.
11. Strong analytical, problem-solving, and communication skills.
12. Eager to learn new technologies and adapt in a fast-paced environment.
13. Strong time management skills and ability to meet deadlines.

Required Hard / Technical Skills

1. Python
2. SQL
3. ETL / ELT Development
4. Database Management (MySQL, PostgreSQL)
5. NoSQL (MongoDB, Redis)
6. Apache Airflow
7. Docker
8. Kubernetes
9. Google Cloud Platform (GCP)
10. Big Data Technologies (Spark, Hadoop)
11. Data Warehousing
12. Git
13. Dagster
14. AI Tools (e.g., ChatGPT) for create ideation and productivity