Data Engineer

About AssetMark

AssetMark is a leading wealth management platform dedicated to empowering independent financial advisors. AssetMark's mission is to enable financial advisors to make a profound difference in the lives of their clients. Over 10,000 advisors partner with AssetMark for our investment offerings, innovative technology, advanced services, and expertise, which they use to delight their clients and grow their businesses. We are an integrated team of technologists, investment professionals, and operations experts working to help our clients stay at the pioneering front of wealth management.

Key Responsibilities

• Data Platform Engineering: Design, build, test, and maintain scalable, reliable, and fault-tolerant ETL/ELT pipelines and reusable platform components across Azure and Snowflake.
• Data Ingestion & Source Onboarding: Integrate complex financial data from internal systems, third-party providers, databases, APIs, and files; support batch and near-real-time ingestion patterns where appropriate.
• Integrations, Data Feeds & MDS Support: Develop and operate inbound and outbound integrations and data feeds, support MDS tools and dependencies, troubleshoot production issues, and help ensure reliable delivery to downstream consumers.
• Data Reliability & Operations: Monitor pipeline health, freshness, volume, schema changes, and failures; respond to incidents, perform root-cause analysis, and improve performance, resilience, recoverability, and cost efficiency.
• Data Quality, Governance & Security: Implement automated validations, documentation, lineage, cataloging, access controls, encryption, and sensitive-data protections in accordance with financial-industry governance and security standards.
• Engineering Practices: Use Python, SQL, and fit-for-purpose data tools to deliver maintainable solutions; follow Git-based workflows, code reviews, testing, automated deployment, and CI/CD standards using platforms such as Azure DevOps or GitHub Actions.
• Business & Technical Collaboration: Partner with product managers, business users, operations teams, data stewards, analysts, and engineers to understand processes, clarify requirements, and translate business needs into scalable technical solutions.
• Global Delivery & Continuous Improvement: Participate actively in agile ceremonies, retrospectives, documentation, and knowledge sharing across the GCC and U.S. teams, and responsibly use AI-assisted engineering methods to improve development, testing, documentation, and troubleshooting.

Knowledge, Skills, Abilities

• Practical experience designing, building, and supporting ETL/ELT pipelines, data ingestion processes, system integrations, and data feeds
• Working knowledge of Python and SQL for data movement, automation, validation, troubleshooting, and operational support
• Experience with cloud data platforms, especially Microsoft Azure and Snowflake
• Familiarity with modern data engineering, governance, and observability tools, including Snowflake, dbt, Fivetran, Monte Carlo, Immuta, and Atlan
• Understanding of orchestration, APIs, database connectivity, file-transfer patterns, scheduling, and dependency management
• Familiarity with medallion architecture and core data modeling concepts used to organize and manage data across platform layers
• Understanding of data quality, lineage, cataloging, access control, privacy, and secure handling of sensitive or regulated data
• Experience with version control, collaborative Git workflows, automated testing, and CI/CD practices
• Strong problem-solving skills and the ability to investigate ambiguous data, integration, platform, or tool issues methodically
• Excellent communication skills and the ability to collaborate across technical and business teams in a hybrid, globally distributed organization
• Experience in wealth management, asset management, financial technology, or a related financial-services domain is a plus

Qualifications & Experience

• 2-5 years of experience in data engineering, data integration, software engineering, platform engineering, or a related technical role
• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical field, or equivalent practical experience
• Experience working with sensitive or regulated financial data and following secure data-handling practices is required

Why Join AssetMark?

• Build global data capabilities from AssetMark's Hyderabad Technology Center, an important part of our India GCC
• Work across a broad data engineering ecosystem that includes the data platform, ingestion, integrations, data feeds, MDS support, quality, governance, and observability
• Work with modern data technologies while learning industry best practices through structured mentorship from experienced engineers
• Develop both technical and business domain expertise in the wealth management industry, with clear advancement pathways as you grow
• Collaborate with colleagues in India and the United States on meaningful technology that supports financial advisors and their clients
• Access comprehensive training resources, workshops, and learning materials designed to accelerate your professional development
• Enjoy comprehensive benefits, competitive compensation, and a supportive work environment that values your growth
• Opportunity to build your career in a high-growth company backed by private equity