Principal Software Engineer

5 days ago

San Francisco, California, United States Project44 Full time
About the Role

As a Principal Software Engineer - Data Engineering at project44, you will have the opportunity to work on the latest technologies to streamline Machine Learning & AI Operations, build scalable data infrastructure, and democratize data access.

Key Responsibilities
  • Work with software architecture and design as part of your job, leveraging and instituting best practices from the areas of distributed systems, databases, data platform, infrastructure, and platform software, manageability, and observability.
  • Provide guidance on new technologies and continuous improvement in best practices, researching, implementing, and developing software development tools.
  • Build systems in a multi-cloud environment, utilizing AWS and GCP, with experience in other cloud environments such as Azure.
  • Build complex metrics solutions with data visualization support for actionable business insights.
  • Leverage expertise in latest Gen AI tools & methodologies like RAG, Vector DB, embeddings to architect and build automated data access & interpretation solutions.
  • Design and development ETL/ELT using Python/Java with Snowflake, Postgres, and other data stores.
  • Develop and automate a project through its entire lifecycle.
  • Knowledge in Data Warehouse/Data Mart design and implementation.
  • Build distributed, reusable, and efficient backend ETLs.
  • Implementation of security and Data protection.
  • Understand repeatable automated processes for building the application, test it, document it, and deploy it at scale.
  • Work collaboratively with insights and data science teams to understand end-user requirements to provide technical solutions and for the implementation of new features and data pipelines.
  • Establish quality processes to deliver a stable and reliable solution.
  • Efficient in writing complex SQL, stored procedures in Snowflake, Postgres, BigQuery.
  • Preparing documentation (Data Mapping, Technical Specifications, Production Support, data dictionaries, test cases, etc.) for all projects.
  • Coach junior team members and help your team to continuously improve by contributing to tooling, documentation, and development practices.
Requirements
  • 8+ Years of experience in leading Data Engineering efforts.
  • 3+ Years of experience in Snowflake, Oracle, and knowledge in No SQL database like MongoDB.
  • 3+ Years of experience in Python/Java.
  • 3+ Years of experience in ETL Developer role with deep knowledge of data processing tools like Airflow, Argo workflow.
  • 4+ yrs experience with data engineering and operations, including administering production-level, always-on, high throughput, complex OLTP RDBMS.
  • Experience in delivering software solutions in areas of distributed systems.
  • Experience with working with Neural network and Gen AI methodologies.
  • Strong experience in building data warehouse solutions and Data Modeling.
  • Strong ETL performance-tuning skills and the ability to analyze and optimize production volumes and batch schedules.
  • Experience with ETL, GCP, Unix/Linux, Helm Charts as well as Git or other version control systems.
  • Experience with PII redaction for traditional ETL pipelines, as well as in GenAI solutions.
  • Expertise in operational data stores and real-time data integration.
  • Expert level skill in modeling, managing, scaling, and performance tuning high-volume transactional database.
  • Bachelor's Degree in computer science or equivalent experience.
Technical Skills
  • Strong programming/scripting knowledge in building and maintaining ETL using Java, SQL, Python, Bash, Go.
  • In-depth hands-on knowledge of public clouds - GCP(preferred)/AWS, PostgreSQL (version 9.6+), ElasticSearch, MongoDB, MySQL/MariaDB, Snowflake, BigQuery.
  • Participate in an on-call rotation to mitigate any data pipeline failures.
  • Strong experience with Kafka or equivalent event/streaming based systems.
  • Experience with Docker, Kubernetes.
  • Experience with RAG, Vector DB, embedbings, etc.
  • Develop and deploy CICD pipelines for Data Engineering.
  • Experience and knowledge of optimizing database performance and capacity utilization to provide high availability and redundancy.
  • Proficiency with high volume OLTP Databases and large data warehouse environments.
  • Ability to work in a fast-paced, rapidly changing environment.
  • Understanding of Agile and its implementation for Data Warehouse Development.

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