Python Application Engineer, Investor Data Sync Platform

Project overviewYou 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.TeamYou 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 overviewWe 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 stackPython, 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, SQLResponsibilitiesDesign and implement serverless Lambda functions in Python with type hints and structured loggingBuild AWS Step Functions state machines for complex multi-step data workflows, including error handling and retry logicExtract data from Snowflake and transform it using PyArrow with attention to memory efficiencyIntegrate with external REST APIs, including Salesforce and other platforms, and manage authentication tokensApply SQL optimization techniques for Snowflake performance tuningImplement correlation tracking and end-to-end observability across pipeline executionsTroubleshoot pipeline issues using Amazon CloudWatch logs and DataDog dashboardsMaintain shared Python utilities in Lambda Layers to improve code reusabilityParticipate in code reviews with a focus on Python best practices and clear designDeploy infrastructure changes using GitHub Actions with tag-based promotion between environmentsRequirementsMore than five years of Python engineering experience, preferably in serverless or cloud-based ecosystemsAbility to write Python code with type hints and apply functional programming patterns where appropriatePractical experience building and consuming REST API clientsAdvanced SQL skills, including complex joins, window functions, common table expressions, and query optimization in SnowflakeHands-on experience with AWS services, including Lambda, Step Functions, DynamoDB, S3, IAM, and CloudWatchExperience using Terraform to define and debug infrastructure as code for AWS resourcesBackground in designing ETL or ELT pipelines with attention to error handling, retries, idempotency, and state managementExperience working with Git based workflows, including CI CD practices, branch strategies, and code review participationAbility to investigate and debug distributed systems using Amazon CloudWatch and DataDog logs and metricsNice to haveExperience with AWS X-Ray or similar distributed tracing toolsExperience building integrations with Salesforce or similar SaaS platformsExperience designing structured logging standards for data pipelinesExperience working with partitioned Parquet files in Amazon S3