Data Analyst

Job Summary: As a Data Engineer, you will play a crucial role in designing, developing, and maintaining the infrastructure and systems necessary for the collection, storage, processing, and analysis of large volumes of data. Your primary responsibility will be to build scalable data pipelines, optimize data workflows, and ensure the availability and reliability of data systems. You will collaborate closely with cross-functional teams, including data scientists, analysts, and software engineers, to support their data-related needs and drive data-driven decision-making across the organization.

Responsibilities:

1. Design, develop, and maintain scalable and efficient data pipelines to acquire, transform, and load large volumes of structured and unstructured data from various sources.
2. Collaborate with data scientists, analysts, and business stakeholders to understand their data requirements and translate them into technical solutions.
3. Implement data governance and quality measures to ensure the accuracy, completeness, and consistency of data.
4. Optimize data workflows and processing systems to improve performance and efficiency.
5. Identify and resolve data-related issues and bottlenecks, ensuring the availability and reliability of data systems.
6. Implement and maintain data security and privacy measures to protect sensitive information.
7. Explore and evaluate new technologies, tools, and frameworks to enhance data engineering capabilities and scalability.
8. Collaborate with cross-functional teams to design and implement data models, schemas, and data architecture.
9. Create and maintain technical documentation, including data flow diagrams, data dictionaries, and system specifications.
10. Stay updated with industry trends and best practices in data engineering and contribute to the continuous improvement of data engineering processes and methodologies.

Qualifications:

1. Bachelor’s or higher degree in Computer Science, Engineering, or a related field.
2. Proven experience as a Data Engineer or in a similar role, working with large-scale data processing and analytics.
3. Strong programming skills in languages such as Python, Java, or Scala.
4. Proficiency in SQL and experience working with relational databases and query optimization.
5. Familiarity with big data processing frameworks and tools like Hadoop, Spark, or Apache Beam.
6. Experience with cloud-based data platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
7. Knowledge of data warehousing concepts and technologies (e.g., Redshift, Snowflake).
8. Understanding of data modeling, data integration, and ETL/ELT processes.
9. Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
10. Excellent problem-solving skills and attention to detail.
11. Strong communication and collaboration abilities to work effectively in a team-oriented environment.