Senior Data Developer/Engineer

Global Technical Talent; Edmonton; Remote; CAD 80,000 - 110,000; Full time

Job summary

An innovative firm is seeking a Senior Data Engineer/Developer to lead the creation of data solutions in the investment domain. This exciting opportunity involves collaborating with investment professionals to design and implement robust data systems that enhance decision-making processes. You will establish a Data Development Center of Excellence, driving innovation and best practices in data engineering. If you have a passion for data and a strong background in investment analytics, this role offers a chance to make a significant impact in a dynamic environment.

Qualifications

• 5+ years of experience in data engineering or similar roles.
• Strong understanding of relational and non-relational databases.

Responsibilities

• Lead the development and management of data solutions for investment.
• Design data models and pipelines for investment-related data.

Skills

Python

SQL

R

Data Engineering

ETL Processes

Data Integration

Data Quality

Investment Analytics

Tools

Azure Data Lake

Azure Data Factory

Databricks

DBT

Job description

Job Title:

Senior Data Engineer/Developer

Job Type:

Contract

Job Duration:

10 months (+1 year extension)

Job Location:

100% Remote - Alberta, CA

Job Duties:

As a Data Development/Engineer, you will be responsible for leading the development and management of data solutions specific to the investment domain. You will work closely with investment professionals, data analysts, and other stakeholders to design and implement data systems that support investment decision-making processes. This role will also involve establishing and growing a Data Development Center of Excellence to foster innovation and best practices in data development for data-driven decisions within the organization.

This role requires strong technical skills in data engineering, investment data analysis, and financial domain knowledge.

1. Investment Data Solution Design: Collaborate with investment teams and data analysts to understand their data requirements and translate them into scalable and robust data solutions. Design data models, pipelines, and integration processes for acquiring, transforming, and storing investment-related data from various sources.
2. Investment Data Integration and Analysis: Develop ETL processes and workflows to gather and combine data from sources like market data providers, trading platforms, and internal systems. Perform data validation, cleansing, and analysis to ensure data accuracy and integrity. Create tools for data visualization and reporting to aid investment analysis and decision-making.
3. Database Management: Design and optimize database structures tailored for investment data storage and retrieval. Ensure efficient indexing, partitioning, and query optimization. Monitor database performance and recommend improvements.
4. Investment Analytics: Work with data analysts and investment professionals to implement analytics models, algorithms, and techniques. Develop data pipelines supporting portfolio analysis, risk assessment, and performance attribution.
5. Data Quality and Governance: Collaborate to establish data quality standards and governance policies specific to investment data. Implement validation, cleansing, and enrichment processes to maintain high data quality. Ensure compliance with relevant regulations and privacy standards.

Mandatory Requirements:

• 5+ years of experience in data engineering, database development, or similar roles, preferably in the investment industry.
• Proficiency in Python, SQL, and R.
• Knowledge of modern big data technologies, including data lakes and data warehouses.
• Understanding of investment data sources like market feeds, trading platforms, and financial databases.
• Familiarity with investment analytics concepts such as portfolio analysis, risk assessment, and attribution.
• Experience with ETL tools, data integration platforms, and visualization tools.
• Experience working with cloud-based systems.
• Strong understanding of relational and non-relational databases, data modeling, and query optimization.
• Knowledge of investment regulations, compliance, and data privacy standards.

Desirable Attributes:

• Experience with Azure Data Lake, Azure Data Factory, Databricks, and DBT is a plus.