ETL Developer with (Apache Airflow, AWS)

Greetings,

TechProjects is a rapidly growing System Integration (SI) and IT staffing company dedicated to providing exceptional value for our clients' time and investment. We offer IT services to a wide array of commercial clients, from small businesses to large corporations, across diverse industries including supply chain & groceries, healthcare, and financial services. Additionally, we serve government entities at the city, state, and other public sector levels, with a particular focus on social services, school systems, and higher education.

Job Title: ETL Developer with (Apache Airflow, AWS)

Location: New Jersey(Hybrid - 3 days Onsite)

Duration: 12 Months

SQL and ETL are mandatory. Good to have DBT experience.

Job Description:

A dbt (data build tool) Developer is responsible for leveraging dbt to transform, model, and manage data within an organization's data analytics stack. dbt Developers play a crucial role in streamlining data workflows, ensuring data accuracy, and providing a structured foundation for data analysis and reporting.

Responsibilities:

1. Data Transformation and Modeling:

- Design and implement data transformations and models using dbt to create structured, cleaned, and aggregated datasets.

- Develop and maintain dbt models that accurately represent business logic and data requirements.

2. SQL Expertise:

- Write and optimize SQL queries within dbt to extract, manipulate, and join data from various sources (e.g., databases, APIs, flat files).

- Ensure SQL code follows best practices for readability, performance, and maintainability.

3. Version Control:

- Use version control systems (e.g., Git) to manage dbt codebase, enabling collaborative development and tracking changes over time.

- Collaborate with data engineers and analysts to coordinate code changes.

4. Testing and Documentation:

- Implement unit tests within dbt to verify the accuracy and reliability of data transformations.

- Document dbt models, data lineage, and transformations to facilitate understanding and collaboration.

5. Automation:

- Schedule and automate dbt runs to keep data models up-to-date and synchronized with source systems.

- Implement data orchestration and scheduling as needed.

6. Data Quality Assurance:

- Develop and enforce data quality checks and validations within dbt to identify and rectify data issues.

- Monitor data quality and integrity, responding to anomalies or discrepancies.

7. Performance Optimization:

- Optimize dbt models and queries for performance, identifying and addressing bottlenecks.

- Analyze and fine-tune data processing pipelines to meet performance requirements.

8. Collaboration:

- Collaborate closely with data engineers, data analysts, and business stakeholders to understand data requirements and deliver data solutions.

- Participate in cross-functional teams and contribute to data-related projects.

9. Security and Compliance:

- Ensure data security and compliance with relevant data protection regulations (e.g., GDPR, HIPAA) through appropriate data handling practices.

10. Knowledge Sharing:

- Share knowledge of dbt best practices and data modeling techniques with team members.

- Provide training and support to data analysts and other users of dbt.

Qualifications:

• Bachelor's or master's degree in computer science, data science, or a related field.
• Strong proficiency in SQL and experience working with relational databases.
• 3+ years of experience using dbt for data transformation and modeling in a data warehouse environment (e.g., Snowflake, BigQuery, Redshift).
• 7+ years of experience building business rules using a business rules engine similar to dbt
• Familiarity with version control systems (e.g., Git) and code collaboration workflows.
• Excellent data analysis and problem-solving skills.
• Strong attention to detail and a commitment to data quality.
• Understanding of data warehousing concepts and best practices.
• Knowledge of data governance and data security principles.
• Effective communication and collaboration skills to work with diverse teams.
• Experience with other data tools and languages (e.g., Python, R, Looker) is a plus

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