About the Role

iCapital is looking to hire an experienced Python Developer with expertise in web scraping, automated portal interactions, and cloud-native deployment using AWS. The ideal candidate will have hands-on experience working with Playwright for browser automation, managing multi-factor authentication (MFA) flows, and deploying scalable scraping tasks via AWS Lambda and related services. This role will assist in architecting and building robust, secure, and scalable scraping solutions that interact with complex web applications and secured portals.

Responsibilities

• Assist with the design and implementation of advanced scraping solutions using Python, Playwright, and AWS services.
• Automate interactions with JavaScript-heavy and authentication-secured websites, including handling MFA, CAPTCHAs, and session or token-based login flows.
• Architect scraping pipelines using serverless AWS components such as Lambda, Step Functions, S3, CloudWatch, and Secrets Manager.
• Build systems that scale to support high volumes of data extraction with fault tolerance, retries, and intelligent logging.
• Integrate and manage complex workflows across multiple portals, APIs, and data sources.
• Contribute to architectural decisions, tooling, and best practices.

Qualifications

• Bachelor’s or master’s degree in computer science, software engineering, or related field, or equivalent professional experience
• 10+ years of experience in Python development, with a strong focus on automation and data extraction
• Proven expertise in web scraping using tools like Playwright, Selenium, Scrapy, BeautifulSoup, and requests
• In-depth experience handling multi-step authentication flows, including multi-factor authentication (MFA), CAPTCHA solving, and session or cookie management
• Proficient in deploying and managing scraping workloads in AWS, particularly Lambda, S3, IAM, CloudWatch, and Secrets Manager
• Experience with asynchronous programming, headless browsers, and JavaScript-rendered content
• Solid understanding of web protocols (i.e. HTTP, HTTPS, cookies, headers), and the ability to reverse-engineer network calls and authentication mechanisms
• Comfortable working with APIs, JSON/XML, and data transformation
• Experience with CI or CD pipelines, Docker, and infrastructure as code (i.e. CloudFormation, Terraform)
• Familiar with data pipeline orchestration tools such as Apache Airflow or AWS Step Functions
• Prior experience scraping from secure or enterprise-level portals (i.e. financial, healthcare, legal)
• Background in data engineering or ETL workflows is a plus
• Exposure to Python testing frameworks and writing unit or integration tests

Benefits

The base salary range for this role is $130,000 to $160,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

This position does not offer visa sponsorship now or in the future.

iCapital is seeking an exceptional Data Engineer to help scale the data foundations that power the business. This individual will design, build, and optimize the data pipelines and infrastructure that enable data to be a strategic asset across the organization. This role is highly collaborative and will partner with the Product, Engineering, Analytics teams and business stakeholders to quickly understand evolving challenges and deliver scalable, maintainable, and high‑quality solutions.

Data sits at the core of iCapital’s operations. The firm relies on clean, reliable, well‑structured data to drive decision‑making, enhance client experiences, and support a rapidly growing product suite. This individual will be responsible for moving and transforming data and developing a deep understanding of the business context behind it and help teams act on insights.

Responsibilities

• Develop and automate large scale, high-performance data platform pipelines and infrastructure to drive iCapital business growth and enable data-driven decision making.
• Design and develop reusable components and frameworks for ingestion, cleansing, and data quality.
• Streamline the ingestion of raw data from various sources into our Data Lake and Data Warehouse.
• Design data models for optimal storage and retrieval that represent the tangible business domains across iCapital’s ecosystem.
• Coordinate closely with the Operations, Sales, and Product Development teams daily to push iCapital’s FinTech strategy and improve the overall profitability of the business.

Qualifications

• 6-10 years of professional experience in a data engineering or data-driven software engineering role
• Exceptional Python and SQL skills
• Extensive experience with orchestration frameworks (Prefect, Airflow, Dagster, etc.)
• Deep understanding of OLAP (Snowflake, Databricks) and OLTP (PostgreSQL, MongoDB) databases and ELT frameworks (dbt, dlthub)
• Experience developing and deploying code to Cloud environments (AWS, GCP, Azure)
• Possess a strong grasp of object-oriented and functional programming and an ability to write easy-to-scale, high-quality code
• Experience leveraging stream processing frameworks (Kafka, Flink, Spark)
• Knowledge of infrastructure-as-code frameworks (terraform or cloud formation)
• Detail-oriented and able to multitask and work in a fast-paced environment
• Able to work independently while also being a strong team player
• Excellent written and verbal communication
• Passionate about learning and mastering cutting-edge technologies
• Professional experience with JVM based languages such as Scala, Java, and Kotlin is preferred
• Knowledge of financial markets and financial instruments is preferred

Benefits

The base salary range for this role is $100,000 to $135,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

The Role

Analytics Engineering at Flex sits at the intersection of Data, Product, Engineering, and business objectives. As Director, Analytics Engineering you will run the team that enables stakeholders at Flex to easily find the data they need to make decisions. You’ll be responsible for developing a world-class analytics platform that powers all data consumption at Flex, as well as managing and developing a team of high-performing Analytics Engineers. You'll also be hands-on, leveraging your technical skills to develop data models and build better data products and solutions. You'll partner with analysts, engineers, PMs and others to define the requirements while being accountable for delivering the end data product.

You Will:

• Develop and lead strategy for data modeling platform and team roadmap
• Manage and mentor a team of Analytics Engineers
• Collaborate with leaders across product & engineering teams to define data requirements and inform architecture/schema design decisions
• Lead the development of data models to consume, transform, and expose data to stakeholders and systems across the company
• Collect business requirements, define successful analytics outcomes, and design data solutions
• Set company-wide standards for data regarding structure, quality, and expectations
• Contribute Flex’s data culture by influencing processes, systems, and tools that enable to make better decisions in a scalable way

You Have:

• 8+ years as an analytics engineer or equivalent, with a track record of shipping high quality products and features at scale
• Expert knowledge of SQL, data warehouses (we use Snowflake), and how to write efficient SQL queries
• Familiarity with common BI tools (preferably Sigma Computing, Tableau, Mode, etc.)
• Expert proficiency with dbt, dbt Cloud, and Airflow
• Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, and best practices for codebase development and CI/CD)
• Proficiency with Python preferred
• Experience within the fintech space preferred

Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area.  

Tier A (NYC/SF/Seattle): $240,000-290,000
Tier B (Austin, Washington D.C. Philadelphia, Los Angeles, San Diego, Chicago, Miami, Atlanta : $215,000-265,000
Tier C (SLC/All Other States): $200,000-250,000

Offices

Roles posted in New York, San Francisco, or Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program.

ABOUT THIS ROLE

As Data Engineer, AI, you will play a key role in building and advancing LVT’s data platform — contributing across the full data engineering lifecycle, from ingestion and transformation to semantic modeling and delivery — while also helping build the data infrastructure that powers LVT’s AI initiatives, including RAG pipelines and Snowflake Cortex models. This is a core engineering role with an AI edge: you’ll keep the data platform running with precision and reliability, and you’ll be the person who makes sure our AI systems have the clean, well-structured data they need to perform.

LVT is a flexible-first company. This role can be performed remotely, with a preference for candidates who can work from our American Fork, UT office.

ROLE RESPONSIBILITIES

• Design, build, and maintain scalable ELT pipelines that move data reliably from source systems into a clean, well-governed data platform.
• Develop and maintain semantic models that expose consistent, trusted business definitions across reporting and analytics surfaces.
• Own data quality — implement validation, monitoring, and alerting frameworks that catch problems before they reach stakeholders.
• Optimize Snowflake performance across ingestion, transformation, and storage, including dynamic tables, clustering, and query tuning.
• Architect and build the data infrastructure required for RAG applications, including vector storage, chunking strategies, and retrieval pipelines.
• Collaborate with AI/ML engineers to support Snowflake Cortex model development with well-structured, context-rich training and inference data.
• Partner with analytics engineers, data scientists, and business stakeholders to translate requirements into durable data solutions.
• Document data architecture, pipeline design, and modeling decisions to support team knowledge and long-term maintainability.

OUR IDEAL CANDIDATE

• Data Engineering Foundation: 5+ years building and maintaining production-grade pipelines using SQL, Python, and modern ELT tools such as dbt, Fivetran, or Airflow.
• Snowflake Proficiency: Deep hands-on experience with Snowflake, including performance optimization, dynamic tables, and familiarity with Cortex AI capabilities.
• Semantic Modeling Experience: Ability to design and maintain semantic or metrics layers that enforce consistent business logic across the organization.
• AI Infrastructure Awareness: Working knowledge of RAG architectures and the data patterns — chunking, embedding, retrieval — that support LLM-driven applications.
• Data Quality Ownership: Strong instinct for reliability — you instrument pipelines with observability and validation from the start.
• End-to-End Mindset: Comfortable owning work from scoping through production — you define the problem, build the solution, and stand behind the outcome.
• Collaborative Communicator: Able to work fluidly with engineers, analysts, and non-technical stakeholders, translating ambiguity into clear data solutions.

About your role

We are looking for a forward-thinking Data Engineering Intern to join our team for Summer 2026. This isn't just a role about moving data from point A to point B; it’s about rethinking how those pipelines are built. You will sit at the intersection of core infrastructure and AI, building robust ETL processes while leveraging AI technologies to automate the very workflows you create.

Your mission is dual-purpose: you will support our Business Intelligence efforts and directly influence our product roadmap by turning raw data into actionable insights through advanced dashboards and automated workflows.

A Day in the Life

• Build & Orchestrate: Design, develop, and maintain ETL pipelines to ingest data into our Snowflake warehouse using Python, SQL, and Airflow.
• AI-Driven Automation: Implement AI-powered solutions to streamline engineering tasks, including:
• Automating code generation and documentation.
• Building AI-driven data quality checks and anomaly detection.
• Developing "self-healing" pipelines that can identify and alert on ingestion errors.
• Insight Generation: Use Jupyter Notebooks and Streamlit to analyze data and build internal tools that help our product team make data-driven decisions.
• Visualization: Create high-impact dashboards in Tableau that translate complex data into a clear narrative for stakeholders.
• Agile Collaboration: Participate in daily Scrum huddles, manage tasks via Jira, and work closely with product owners and QA to promote code to production.
• Cloud Infrastructure: Interact with cloud services via CLI and manage containerized environments using Docker and Kubernetes.

What you’ll need

• Academic Status: Currently pursuing an undergraduate degree with a targeted graduation date in 2026 or early 2027, or pursuing a degree in Computer Science, Data Science, or a related quantitative field.
• Programming Mastery: Expertise in Python and SQL
• Infrastructure Mindset: A strong understanding of Data Warehousing (Snowflake) and ETL orchestration (Airflow).
• DevOps Curiosity: Familiarity with CLI, Docker, and Kubernetes for managing cloud-based environments.
• Analytical Toolkit: Experience with Jupyter Notebooks, Tableau, or Streamlit.
• Problem Solver: A proactive approach to using AI/LLMs to automate repetitive tasks and improve system reliability.

The Summer "Win"

By the end of your 10-week internship, you will have designed and deployed a functional ETL pipeline that feeds into a custom Insights Dashboard. Your work won't just sit in a folder, it will be used to influence our official product roadmap.

Interview Process

• Recruiter Phone Screen
• Technical Assessment 
• Hiring Manager Interview
• Team Interview

About the Role

We’re looking for a Senior Data Engineer to design, build, and optimize our data platforms so teams across the company can make fast, reliable, data-driven decisions. You’ll be a key technical leader, owning end-to-end data pipelines and modeling, and setting best practices around how we work with data.

You’ll work heavily with Databricks, Spark, SQL, and Python, building scalable data solutions that power analytics, reporting, and data products. Experience in payments or financial services is a strong plus.

What You’ll Do

• Design and build data pipelines
• Develop, maintain, and optimize ETL/ELT pipelines on Databricks and Spark.
• Integrate data from multiple internal and external sources into a centralized data platform.
• Own data modeling & architecture
• Design and maintain robust data models (e.g., star/snowflake schemas, data vault, dimensional models) to support analytics and self-service BI.
• Establish and enforce data modeling standards and documentation.
• Ensure data quality, reliability, and performance
• Implement data quality checks, validation frameworks, and monitoring.
• Tune queries and jobs for performance and cost efficiency in Databricks and downstream systems.
• Collaborate and lead
• Partner with data analysts, data scientists, and product/engineering teams to understand data needs and translate them into technical solutions.
• Provide technical leadership and mentorship to other data engineers; help review designs and code.
• Governance & best practices
• Contribute to and refine our data governance, security, and access control practices.
• Drive best practices around version control, CI/CD for data, and code standards.

Required Qualifications

• 7+ years of professional experience as a Data Engineer, Software Engineer, or similar role.
• Strong hands-on experience with Databricks (or a very similar cloud data platform) including cluster management, jobs, and notebooks.
• Advanced experience with Apache Spark for batch and/or streaming data processing.
• Expert-level SQL skills (complex joins, window functions, query optimization).
• Strong Python skills for data engineering (e.g., PySpark, data processing libraries, scripting).
• Proven experience in data modeling and designing schemas for analytics and reporting.
• Experience building and maintaining data pipelines in a cloud environment (AWS, Azure, or GCP).
• Strong understanding of data warehousing concepts, ETL/ELT best practices, and data lifecycle.
• Solid software engineering fundamentals: version control (git), testing, code reviews, and CI/CD.
• Excellent communication skills and the ability to collaborate with technical and non-technical stakeholders.

Nice to Have

• Experience in payments, fintech, banking, or broader financial services (e.g., transaction data, ledgers, risk, fraud, reconciliation).
• Experience with streaming technologies (e.g., Spark Structured Streaming, Kafka, Kinesis, or similar).
• Familiarity with dbt or similar transformations-as-code frameworks.
• Experience with orchestration tools (e.g., Airflow, Databricks Workflows).
• Knowledge of BI tools (e.g., Power BI, Tableau, Looker) and how data models power them.
• Exposure to machine learning workflows and supporting data science teams.
• Experience implementing data governance, lineage, and catalog tools.

What You’ll Bring

• A product mindset: you think about the end users of data and build with usability in mind.
• A bias for automation, reliability, and scalability over one-off solutions.
• Comfort with ambiguity, ownership of complex problems, and a desire to continuously improve the data ecosystem.

What We Offer

• 401k investment opportunity, with company match   
• Medical, Dental, and Vision Plans
• Paid Time Off   
• Paid Parental Leave
• Paid Volunteer Leave

Role Information: 

• Full-Time, On-site, Provo

ABOUT THIS ROLE 

As the Sr. Manager of Data Engineering and Architecture, you will be a hands-on leader responsible for defining and executing the data engineering strategy, architecture, and technology stack. You will be responsible for the foundational data infrastructure that powers analytics and decision-making across the organization.

A critical part of this role will be building, mentoring, and managing a team of 3 data engineers. You will guide the team's efforts while also contributing directly to the development of our modern data warehouse in Snowflake using dbt and SQL, transforming raw data into reliable and accessible datasets. Crucially, you will spearhead the data migration efforts for our ongoing Oracle Fusion Cloud deployment, designing a robust, cohesive data ecosystem that bridges our new Oracle environment with Snowflake.

Your leadership will ensure the successful design, build, and maintenance of robust data pipelines that ingest data from a variety of internal and external sources into Snowflake. Your team's work will support reporting, dashboarding, and analysis across the company, enabling teams to make informed decisions based on trusted data. Given the green-field nature of this initiative, the role is expected to be approximately 30% technical leadership, strategy, and people management, and 70% direct, hands-on engineering and architecture.

This position is based in a hybrid work environment and requires regular in-office collaboration. It offers an opportunity to lead with modern data tools, build a high-performing team, and make a direct, strategic impact on data quality and accessibility during a massive phase of enterprise scaling.

ROLE RESPONSIBILITIES

• Data Strategy & Architecture: Define the long-term vision, strategy, and architecture for the company’s data platform. Design a cohesive hybrid architecture that maximizes the strengths of our full tech stack, ensuring it drives measurable business value and scales efficiently to support hyper-growth.

• Team Leadership & Management: Build, mentor, and manage a team of 3 data engineers, fostering a culture of technical excellence, accountability, and continuous improvement.

• Data Modeling & Transformation: Lead the team in building and maintaining robust data models using dbt and SQL that support complex analytics and reporting needs. Contribute directly as an individual contributor as needed.

• Snowflake Development: Oversee the design and optimization of the Snowflake data warehouse to ensure performance, scalability, and usability. Participate directly in key development efforts.

• Cross-Functional Collaboration: Act as the primary technical partner to analysts, business stakeholders, and data teams to deeply understand requirements and translate them into strategic engineering solutions and delivery plans.

• Performance Tuning: Guide the optimization of SQL queries and data transformations to improve execution speed and resource efficiency across the platform.

• Tooling & Automation: Identify, evaluate, and implement opportunities to automate data workflows, improve pipeline reliability, and establish a formal DataOps/MLOps framework using modern orchestration tools (e.g., Airflow, Prefect, cloud-native serverless functions).

• BI Tool Support: Ensure the team provides clean, well-structured data models to enable effective use of BI tools like Looker, Sigma, Tableau, or similar platforms.

• Pipeline Engineering: Direct the development and maintenance of scalable data ingestion pipelines that pull data from APIs and other sources into Snowflake, including exploring solutions for near real-time data feeds.

• Data Governance & Quality: Champion best practices in data governance, data lifecycle management, and dimensional modeling. Implement data validation checks, documentation standards, and lineage tracking to maintain high data integrity across all of our systems.

• Oracle Fusion Cloud Migration & Integration: Lead the complex data migration strategy for our active Oracle deployment. Architect, build, and maintain secure, high-performing data flows and syncs between Oracle and Snowflake to ensure operational continuity and analytical excellence.

OUR IDEAL CANDIDATE

• Experience: 8+ years in data engineering or related roles, with a strong focus on data modeling and pipeline development.

• Education: Bachelor’s degree in Computer Science, Engineering, Data Analytics, or a related field.

• Technical Skills:

  • Proven experience leading complex data migration or implementation projects.

  • Advanced proficiency in SQL and experience with data modeling (e.g., star/snowflake schemas).

  • Hands-on experience with dbt for building modular and testable data transformations.

  • Experience developing data pipelines using Python and workflow orchestration tools (e.g., Airflow, Prefect).

  • Deep understanding of Snowflake.

  • Demonstrated ability to design and implement a modern data architecture from scratch.

• BI & Analytics Tools:

  • Familiarity with BI platforms such as Looker, Tableau, or Sigma is helpful.

• Infrastructure & Governance:

  • Understanding of ELT/ETL workflows, data governance, and monitoring practices.

  • Experience defining and enforcing organizational standards for data quality, metadata management, and cost optimization within a cloud data warehouse (Snowflake).

• Communication & Problem Solving:

  • Ability to clearly explain technical details to both technical and non-technical stakeholders.

  • Strong analytical and debugging skills; attention to detail in code and data quality.