Data Operations Engineer - Denver CO - Fulltime

Role: Data Operations Engineer

Location: Denver CO

Job Description:

Managing and optimizing the flow of data within Airlines. The roles and responsibilities of the Data Operations Engineer are listed below

Roles and responsibilities:

1. Data Integration: Designing implementing and maintaining data integration processes. Ensuring smooth data flow between different systems and databases. Managing ETL (Extract Transform Load) and ELT (Extract Load and Transform) processes.

2. Data Quality Management: Implementing and maintaining data quality standards. Identifying and resolving data quality issues. Collaborating with data stewards to improve data quality.

3. Data Warehousing: Maintaining data warehouses. Optimizing data storage and retrieval processes. Managing and monitoring data warehouse performance.

4. Data Governance: Establishing and enforcing data governance policies. Collaborating with stakeholders to define data ownership and access policies. Ensuring compliance with data privacy regulations.

5. Data Security: Implementing and monitoring data security measures. Managing access controls and permissions. Conducting regular security audits and assessments.

6. Data Monitoring and Troubleshooting: Monitoring data pipelines for errors and anomalies. Investigating and resolving datarelated issues. Implementing proactive measures to prevent data problems.

7. Performance Optimization: Tuning and optimizing database and data processing performance. Identifying and resolving bottlenecks in data pipelines. Implementing best practices for data performance.

8. Collaboration: Collaborating with crossfunctional teams business stakeholders. Participating in datarelated projects and initiatives. Providing support to endusers.

9. Documentation: Documenting data processes workflows and configurations. Creating and maintaining documentation for datarelated policies and procedures.

Skills Required:

Expertise in Data store architectures like Modern data warehouse (MDW) and Lakehouse architecture.

Must be familiar with extract load transform (ELT) and extract transform load (ETL) tools.

Should have solid knowledge of data processing languages including SQL and Python

Should be proficient in using the following to create data processing solutions: SSIS Azure Data Factory (ADF) Azure Synapse Analytics Azure Event Hubs Azure Data Lake Storage Azure Databricks.

Strong analytical and criticalthinking skills.

Domain knowledge related to the industry they are working in.

Effective communication skills to convey complex data insights to nontechnical stakeholders