Senior Data Developer/Engineer

Global Technical Talent; Edmonton; Remote; CAD 80,000 - 120,000; Full time

Job summary

A leading company is seeking a Senior Data Engineer/Developer for a remote contract position focused on investment data solutions. The role involves designing data systems, integrating data sources, and establishing governance standards to enhance data-driven decision-making. Candidates should have a strong background in data engineering with expertise in programming languages such as Python and SQL, and a solid understanding of investment data landscapes.

Qualifications

• 5+ years experience in data engineering, preferably in the investment industry.
• Strong proficiency in Python, SQL, and R.
• Familiar with modern big data technologies including data lakes.

Responsibilities

• Lead development and management of data solutions for investment.
• Design data models and implement data systems to support decision-making.
• Establish data quality standards and governance policies.

Skills

Data Engineering

Database Development

Investment Data Analysis

ETL Processes

Data Visualization

Cloud Systems

Tools

Python

SQL

R

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 managing 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 lead the establishment and growth of a Data Development Center of Excellence to foster a culture of innovation and implement best practices in data development to support our data-driven decision-making process within the organization. This role requires strong technical skills in data engineering, investment data analysis, and financial domain knowledge.

• 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, data pipelines, and integration processes to acquire, transform, and store investment-related data from various sources.
• Investment Data Integration and Analysis: Develop ETL processes and data integration workflows to gather and combine data from different sources such as market data providers, trading platforms, and internal systems. Perform data analysis, data validation, and data cleansing to ensure data accuracy and integrity. Develop tools and frameworks for data visualization and reporting to support investment analysis and decision-making.
• Database Management: Design and optimize database structures and schemas specifically tailored for investment data storage and retrieval. Ensure efficient data indexing, partitioning, and query optimization techniques are implemented to support fast and accurate data retrieval. Monitor database performance and make recommendations for improvements.
• Investment Analytics: Collaborate with data analysts and investment professionals to identify and implement investment analytics models, algorithms, and techniques. Develop data pipelines and workflows to support portfolio analysis, risk assessment, performance attribution, and other investment-related analytics tasks.
• Data Quality and Governance: Collaborate with cross-functional teams to establish data quality standards and data governance policies specific to investment data. Implement data validation, data cleansing, and data enrichment processes to maintain high-quality investment data. Ensure compliance with regulatory requirements and industry best practices related to investment data management and privacy.

Mandatory Requirements:

• Solid experience (5+ years) in data engineering, database development, or a similar role, preferably within the investment industry.
• Strong proficiency in programming languages like Python, SQL, and R.
• Excellent understanding of modern big data technologies including data lakes and data warehouses with knowledge of the underlying architecture
• In-depth knowledge of investment data sources, such as market data feeds, trading platforms, and financial databases.
• Familiarity with investment analytics concepts, including portfolio analysis, risk assessment, and performance attribution.
• Experience with ETL tools, data integration platforms, and data visualization tools
• Proven experience of working with cloud-based system
• Strong understanding of relational and non-relational databases, data modeling, and query optimization.
• Knowledge of investment regulations, compliance requirements, and data privacy regulations in the investment industry.

Desirable Attributes:

• Hands on experience in the following technology stack: Azure Data Lake, Azure Data Factory, Databricks, and DBT is a asset

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