Python Application Engineer, Investor Data Sync Platform

Project overview

You will work on a data integration platform that orchestrates investor data flows across cloud systems. The platform uses serverless architecture to coordinate data pipelines between Snowflake, Salesforce, and API driven services. The focus is on reliable execution of complex workflows across development, QA, and production environments.

Team

You will collaborate with Python engineers, data engineers, and cloud specialists who are responsible for designing, implementing, and supporting serverless data solutions. The team works in an iterative delivery model, reviews each other’s code, and shares ownership of pipeline quality, observability, and performance.

Position overview

We are looking for a Python Application Engineer who will design, build, and maintain serverless applications that orchestrate data pipelines. You will architect multi step workflows, optimize data transformations, and make sure that pipelines run reliably across development, QA, and production environments.

Technology stack

Python, AWS Lambda, AWS Step Functions, PyArrow, Snowflake, Terraform, GitHub Actions, DynamoDB, Amazon CloudWatch, DataDog, AWS X Ray, REST APIs, Salesforce, Anduin IDM, Amazon S3, Parquet, SQL

Responsibilities

• Design and implement serverless Lambda functions in Python with type hints and structured logging

• Build AWS Step Functions state machines for complex multi-step data workflows, including error handling and retry logic

• Extract data from Snowflake and transform it using PyArrow with attention to memory efficiency

• Integrate with external REST APIs, including Salesforce and other platforms, and manage authentication tokens

• Apply SQL optimization techniques for Snowflake performance tuning

• Implement correlation tracking and end-to-end observability across pipeline executions

• Troubleshoot pipeline issues using Amazon CloudWatch logs and DataDog dashboards

• Maintain shared Python utilities in Lambda Layers to improve code reusability

• Participate in code reviews with a focus on Python best practices and clear design

• Deploy infrastructure changes using GitHub Actions with tag-based promotion between environments

Requirements

• More than five years of Python engineering experience, preferably in serverless or cloud-based ecosystems

• Ability to write Python code with type hints and apply functional programming patterns where appropriate

• Practical experience building and consuming REST API clients

• Advanced SQL skills, including complex joins, window functions, common table expressions, and query optimization in Snowflake

• Hands-on experience with AWS services, including Lambda, Step Functions, DynamoDB, S3, IAM, and CloudWatch

• Experience using Terraform to define and debug infrastructure as code for AWS resources

• Background in designing ETL or ELT pipelines with attention to error handling, retries, idempotency, and state management

• Experience working with Git based workflows, including CI CD practices, branch strategies, and code review participation

• Ability to investigate and debug distributed systems using Amazon CloudWatch and DataDog logs and metrics

Nice to have

• Experience with AWS X-Ray or similar distributed tracing tools

• Experience building integrations with Salesforce or similar SaaS platforms

• Experience designing structured logging standards for data pipelines

• Experience working with partitioned Parquet files in Amazon S3