The Data Engineer role presents a unique opportunity to leverage your expertise and experience in contributing to a mission-driven organization with a global impact. As part of the Portfolio and Data Analytics (PDA) Team, you will work on EQORIS, the organization’s central data platform, and play a crucial role in advancing Enabling Qapital’s data capabilities and infrastructure. Upon joining, the Data Engineer will participate in a comprehensive induction period designed to provide a deep understanding of EQ’s business model, operational processes, procedures, and methodologies. This foundational knowledge will enable you to effectively apply your technical skills to develop further and enhance EQ’s analytical data environment and infrastructure.

The role\'s key functions are centered on three main pillars:

Data Modelling & Engineering

• Data Acquisition - managing ETL/ELT platforms for investment monitoring, portfolio management, and research, capable of handling large datasets; includes indexing data at EQ for reusability and discoverability.
• Data Governance - cataloging the thousands of datasets at EQ to enable discovery, managing access rights, maintaining data quality, and tracking complete data lineage.
• Implement data quality checks, testing, and version control for analytics workflows.
• Partner with data engineers to ensure data pipelines are reliable, efficient, and accurate.
• Design, build, and maintain scalable data models (e.g., using dbt or similar frameworks).
• Transform raw data into structured, well-documented datasets in the data warehouse.

Analytics & Reporting

• Work with data analysts and business stakeholders to design dashboards and reports that track key metrics.
• Support business units/departments with ad hoc data needs and analysis requests.
• Empower end users with self-service data capabilities by building reusable datasets and clear documentation.

MIS

• Collaborate with engineering and analytics teams to ensure the MIS platform is robust, scalable, and adaptable to evolving business needs, including managing the integration of new data sources and expanding the analytical capabilities to meet emerging requirements.
• Collaborate with key business stakeholders and department heads to understand their information needs and translate them into effective, data-driven MIS solutions.
• Data Optimization - Continuously refining data workflows to improve performance, storage efficiency, and processing speed. This includes implementing best practices for query optimization, resource utilization, caching strategies, and data lifecycle management to minimize latency and reduce costs.
• Support MIS Infrastructure - Collaborate with engineering and analytics teams to ensure the MIS platform is robust, scalable, and adaptable to evolving business needs.

The successful candidate will be expected to stay current on the latest data analysis tools, techniques, and industry trends while also actively participating in continuous learning and development activities.

Who you are

We are looking for a highly motivated and outspoken candidate with working experience in financial data science and a compelling personal background. Key attributes and skills you bring to this exciting role are:

Essential Skills

• Bachelor\'s Degree holder in a STEM field
• 3+ years of professional experience in software engineering
• Professional communication and presentation skills, with excellent written and spoken English.
• Experience building reliable, production-grade applications.
• Strong SQL and data modelling skills (experience with dbt or similar is highly desirable).
• Hands-on experience with cloud data warehouses (Snowflake, Redshift, BigQuery, or similar).
• Strong interest in tackling data-related challenges at scale.
• Mastery of (at least) one programming language, modern software engineering principles, and clean code practices. Preferably experienced in Python, SQL (including T-SQL), or PySpark.
• Self-organised with the ability to manage time across multiple projects effectively, despite competing business demands and priorities.

Advantageous

• Deep knowledge of data modelling, data lakehouses, and medallion architecture
• Experience working with large and unstructured datasets.
• Hands-on experience with financial data vendors and understanding of market data structures.
• Stakeholder management skills with proven ability to work effectively across different teams and seniority levels internally and externally.
• Confident communicator: able to argue a point concisely and deal positively with conflicting views.
• Experience with our tooling stack: Linux / UNIX, Docker, Apache Airflow etc.
• Contributions to open-source projects or a strong GitHub Portfolio.

Whom will you work with

The Data Engineer will work closely with the Data Analytics Team.  They will also liaise with EQ’s Risk Management team to highlight key risks and support the Senior Management Team in gaining an overview of EQ\'s overall data analytics process.

What we offer:

• This position is a full-time, fully remote role that involves periodic travel to EQ’s main offices/offshore locations.
• All essential equipment for your role, including laptop, monitor, and communication allowance.
• Opportunities for professional development and advancement.

Location

Remote Role: Preferably in India (Bangalore) or Pakistan (Karachi).English