Senior Data Manager

Our client is a leading financial services firm specializing in trading, finance, accounting, treasury, and pricing data.

They are committed to maintaining the highest data quality standards, governance, and lineage to support their global operations.

They are seeking a Data Ops Manager to join their dynamic team and contribute to their data management and quality initiatives.

The ideal candidate will have a strong background in data management, data quality, and data governance, with a focus on building and maintaining modern data pipelines. This role involves working closely with various teams to ensure data integrity, reliability, and accessibility across the organization.

Key Responsibilities:

• Develop and implement data governance and data quality frameworks, focusing on data lineage, data profiling, and data cataloging.
• Design and maintain ETL/ELT processes to ensure efficient data movement and transformation across systems.
• Implement data quality checks, anomaly detection, and validation processes using tools such as Soda, Great Expectations, and Monte Carlo.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and ensure data accuracy and consistency.
• Integrate data quality checks within data pipelines using tools like Airflow and Kafka.
• Manage and monitor data workflows, ensuring timely and accurate data processing.
• Develop dashboards and reports to visualize data quality metrics and trends for management.
• Provide technical support and guidance to the data engineering team on best practices for data management and data quality.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Domain experience working with Time Series data as it relates to trading.
• Minimum of 5 years of experience in data management, data quality, and data governance.
• Strong experience with data quality tools such as Soda, Great Expectations, or Monte Carlo.
• Proficiency in ETL/ELT processes and tools, including Airflow, Kafka, and Informatica.
• Experience with cloud-based data platforms, preferably AWS, including S3, Postgres (Aurora), and time series databases.
• Skills in Python, with experience in data processing libraries and frameworks.
• Experience with data cataloging tools such as Colibra, Atlan, or BigID.
• Excellent problem-solving skills and attention to detail.
• Strong communication and interpersonal skills, with the ability to work effectively with cross-functional teams.

Preferred Qualifications:

• Experience with financial trading data, including pricing data, energy data, and transactional data.
• Familiarity with machine learning models for data anomaly detection and standard deviation checks.