Senior Data Engineer

ABOUT US:

 

As a world leading provider of integrated solutions for the alternative investment industry, Alter Domus (meaning “The Other House” in Latin) is proud to be home to 90% of the top 30 asset managers in the private markets, and more than 6,000 professionals across 24 jurisdictions.

 

With a deep understanding of what it takes to succeed in alternatives, we believe in being different in what we do, how we work, and most importantly in how we enable and develop our people. Invest yourself in the alternative, and join an organization where you progress on merit, where you can speak openly with whoever you are speaking to, and where you will be supported along whichever path you choose to take. 

 

Find out more about life at Alter Domus at careers.alterdomus.com  

 

JOB DESCRIPTION:

 

Join our dynamic and innovative team as a Senior Data Engineer, where you will collaborate on the design, architecture, and optimization of our enterprise data infrastructure and pipelines. As a senior member of the team, you will provide technical leadership and mentorship while working closely with business stakeholders and the rest of the data team to ensure data is reliable, efficient, secure, and accessible at scale. You will drive best business practices, influence architectural decisions, and play a key role in shaping our data engineering strategy.

 

Key Responsibilities:

1. 1. Data Pipeline Orchestration
      • Design, architect, and maintain complex end-to-end data pipelines using Airflow (including managed services like Amazon MWAA) to orchestrate, schedule, and monitor batch/streaming workflows at enterprise scale.
      • Develop and optimize sophisticated DAGs (Directed Acyclic Graphs) with advanced retry logic, error handling, alerting, and monitoring to ensure maximum data quality and pipeline reliability.
      • Establish best practices and standards for pipeline development, testing, and deployment across the organization.
   2. Data Ingestion & Transformation
      • Architect and implement scalable data integration solutions using Airbyte for ingestion and dbt for transformations in a modular, maintainable fashion.
      • Collaborate with Data Analysts and Data Scientists to design and implement complex transformations and business logic, ensuring data is analytics-ready and optimized for performance.
      • Mentor junior engineers on data ingestion patterns and transformation best practices.
   3. Data Modeling & Warehousing

1. 1. • Design and implement sophisticated data models and architectures for both structured and semi-structured data across AWS S3 (data lake) and Snowflake (data warehouse).
      • Databricks implementations for advanced data processing, analytics, and real-time insights capabilities.
      • Ensure data schemas and transformations support advanced analytics, BI reporting, machine learning use cases, and emerging business needs.
      • Drive data architecture decisions and provide technical guidance on data modeling strategies.
   2. Data Governance & Security
      • Lead implementation of AWS Lake Formation APIs and enterprise-level best practices to maintain data security, access controls, and regulatory compliance.
      • Partner with IT security and compliance teams to establish and enforce robust encryption standards, comprehensive audit trails, and identity/role-based access controls.
      • Champion data governance initiatives and establish data quality frameworks across the organization.
   3. Performance Optimization & Cost Management
      • Lead optimization efforts for AWS Athena queries and configurations (e.g., data partitioning, indexing strategies) for superior performance and cost efficiency.
      • Monitor, analyze, and tune Airflow DAGs, Snowflake queries, and Databricks jobs to maximize throughput, reliability, and cost-effectiveness.
      • Implement monitoring and alerting solutions to proactively identify and resolve performance bottlenecks.
   4. Technical Leadership & Stakeholder Management
      • Provide technical leadership and mentorship to junior and mid-level data engineers, fostering a culture of continuous learning and excellence.
      • Lead cross-functional partnerships with DevOps, Platform Engineering, Da