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🔥 Staff Automation & Data Engineer

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 114000.0 - 171599.0 USD per year

🔍 Fintech

🔧 Requirements

Strong expertise in data pipeline development (ETL/ELT) and workflow automation.
Proficiency in Python, SQL, and scripting languages for data processing and automation.
Hands-on experience with Workato, Google Apps Script, and API-driven automation.

💡 Responsibilities

Automate customer support, success, and service workflows to improve speed, accuracy, and responsiveness.
Build and maintain scalable ETL/ELT pipelines to ensure real-time access to critical customer data.
Implement self-service automation to enable customers and internal teams to quickly access information.

Python SQL ETL Jira API testing Data engineering CI/CD RESTful APIs Data visualization Scripting Customer Success

Posted 1 day ago

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🔥 Senior Data Engineer (Remote from EU)

Posted 2 days ago

📍 Germany, Austria, Italy, Spain, Portugal

🔍 Financial and Real Estate

🏢 Company: PriceHubble👥 101-250💰 Non-equity Assistance over 3 years agoArtificial Intelligence (AI)PropTech Big Data Machine Learning Analytics Real Estate

🔧 Requirements

3+ years of experience building and maintaining production data pipelines.
Excellent English communication skills, both spoken and written, to effectively collaborate with cross-functional teams and mentor other engineers.
Clear writing is key in our remote-first setup.
Proficient in working with geospatial data and leveraging geospatial features.

💡 Responsibilities

Work with backend engineers and data scientists to turn raw data into trusted insights, handling everything from scraping and ingestion to transformation and monitoring.
Navigate cost-value trade-offs to make decisions that deliver value to customers at an appropriate cost.
Develop solutions that work in over 10 countries, considering local specifics.
Lead a project from concept to launch with a temporary team of engineers.
Raise the bar and drive the team to deliver high-quality products, services, and processes.
Improve the performance, data quality, and cost-efficiency of our data pipelines at scale.
Maintain and monitor the data systems your team owns.

AWS Docker Leadership PostgreSQL Python SQL Apache Airflow Cloud Computing Data Analysis ETL Git Kubernetes Apache Kafka Data engineering Data science Spark CI/CD Problem Solving RESTful APIs Mentoring Linux Excellent communication skills Teamwork Cross-functional collaboration Data visualization Data modeling Data management English communication

Posted 2 days ago

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🔥 Senior Analyst, Internal Audit - Data Scientist (L09)

Posted 2 days ago

📍 India

🧭 Full-Time

🔍 Internal Audit

🏢 Company: careers

🔧 Requirements

Minimum 3+ years of experience writing and optimizing SQL/SAS queries in a business environment or 5+ years of experience in lieu of a degree
Knowledge of data warehouse technical architecture, ETL and analytic tools in extracting unstructured and structured data
Experience in building algorithms and coding proficiency in Python is required
Experience with visualization software Tableau or Power BI
Experience managing, moving, and manipulating data from multiple sources
Familiar with segmentation techniques such as decision trees or k-means clustering
Familiar with model development techniques such as logistic regression, random forest, or gradient boosting
Ability to provide analytic support including pulling data, preparing analysis, interpreting data, making strategic recommendations, and presenting to client/product team
Ability to clearly explain technical and analytical information (verbally, written, and in presentation form) and summarize for key stakeholders
Outstanding communications, relationship building, influencing, and collaboration skills
Strong project management, communications, multi-tasking, ability to work independently

💡 Responsibilities

Deliver advanced analytics to support the audit plan, including cycle audits, issue validation, remediation activities and special projects
Design and deploy analytic scripts and dashboards to communicate actionable insights to audit stakeholders.
Document analytic results and findings into audit workpapers.
Ensure the accuracy and integrity of data used in audit engagements through data transformation techniques.
Deploy automation on repetitive audit tasks using data analytics and data engineering techniques.
Collaborate with Internal Audit teams to understand audit test objectives and data requirements.
Collaborate with remediation teams to ensure data insights are effectively integrated into action plans.
Lead projects from beginning to end, including ideation, data mining, strategy formulation, and presentation of results and recommendations.

Python SQL Data Analysis Data Mining ETL Excel VBA Machine Learning Numpy SAS EG Tableau Algorithms Data engineering Data science Pandas RESTful APIs MS Office Data visualization Data modeling

Posted 2 days ago

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🔥 Staff Data Engineer

Posted 2 days ago

📍 United States

🏢 Company: ge_externalsite

🔧 Requirements

Hands-on experience in programming languages like Java, Python or Scala and experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or HiveQL
Exposure to industry standard data modeling tools (e.g., ERWin, ER Studio, etc.).
Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend
Exposure to industry standard data catalog, automated data discovery and data lineage tools (e.g., Alation, Collibra, etc., )
Experience with Big Data / Hadoop / Spark / Hive / NoSQL database engines (i.e. Cassandra or HBase)
Exposure to unstructured datasets and ability to handle XML, JSON file formats
Conduct exploratory data analysis and generate visual summaries of data. Identify data quality issues proactively.
Developing reusable code pipelines through CI/CD.
Hands-on experience of big data or MPP databases.
Developing and executing integrated test plans.

💡 Responsibilities

Be responsible for identifying solutions for complex data analysis and data structure.
Be responsible for creating digital thread requirements
Be responsible for change management of database artifacts to support next gen QMS applications
Be responsible for monitoring data availability and data health of complex systems
Understand industry trends and stay up to date on associated Quality and tech landscape.
Design & build technical data dictionaries and support business glossaries to analyze the datasets
This role may also work on other Quality team digital and strategic deliveries that support the business.
Perform data profiling and data analysis for source systems, manually maintained data, machine or sensor generated data and target data repositories
Design & build both logical and physical data models for both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) solutions
Develop and maintain data mapping specifications based on the results of data analysis and functional requirements
Build a variety of data loading & data transformation methods using multiple tools and technologies.
Design & build automated Extract, Transform & Load (ETL) jobs based on data mapping specifications
Manage metadata structures needed for building reusable Extract, Transform & Load (ETL) components.
Analyze reference datasets and familiarize with Master Data Management (MDM) tools.
Analyze the impact of changes to downstream systems/products and recommend alternatives to minimize the impact.
Derive solutions and make recommendations from deep dive data analysis proactively.
Design and build Data Quality (DQ) rules.
Drives design and implementation of the roadmap.
Design and develop complex code in multiple languages.
This role may also work on other Quality team digital and strategic deliveries that support the business.

PostgreSQL Python SQL Data Analysis ETL Hadoop Java MySQL Oracle Data engineering Nosql Spark CI/CD Agile methodologies JSON Scala Data visualization Data modeling

Posted 2 days ago

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🔥 Senior Data Engineer (R&D team)

Posted 2 days ago

📍 Poland, Ukraine, Cyprus

🧭 Full-Time

🔍 Software Development

🏢 Company: Competera👥 51-100💰 $3,000,000 Seed about 1 year agoArtificial Intelligence (AI)Big Data E-Commerce Retail Machine Learning Analytics Retail Technology Information Technology Enterprise Software Software

🔧 Requirements

5+ years of experience in data engineer role.
Strong knowledge of SQL, Spark, Python, Airflow, binary file formats.

💡 Responsibilities

Contribute to the development of the new data platform.
Collaborate with platform and ML teams to create ETL pipelines that efficiently deliver clean and trustworthy data.
Engage in architectural decisions regarding the current and future state of the data platform.
Design and optimize data models based on business and engineering needs.

Python SQL ETL Kafka Airflow Spark Data modeling

Posted 2 days ago

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🔥 Data Modeller

Posted 2 days ago

📍 UK

🧭 Full-Time

💸 35000.0 - 40000.0 GBP per year

🔍 Banking

🏢 Company: Tandem Bank👥 11-50 Financial Services Banking Finance

🔧 Requirements

Data Modelling
Version Control: Proficient with GitHub for version control and collaboration
Data Transformation: Experience with DBT for data transformation and modelling
Pipeline Orchestration: Working knowledge of Mage.ai for data pipeline development
Database Systems: Experience with Microsoft SQL Server, and time-series data modelling
Business Intelligence: Proficiency in Power BI for semantic modelling and reporting

💡 Responsibilities

Design and implement dimensional and relational data models for business intelligence and analytics use cases
Create and maintain data documentation, including entity-relationship diagrams and data dictionaries
Develop and implement data quality controls and validation procedures
Support the optimisation of data pipelines for data transformation processes
Participate in code reviews and maintain modelling best practices

Python Business Intelligence ETL Microsoft SQL Server Data modeling Data management

Posted 2 days ago

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🔥 Data Intelligence Manager

Posted 2 days ago

📍 United States of America

💸 94510.99 - 150972.31 USD per year

🔍 Banking

🏢 Company: external

🔧 Requirements

6-8+ years in relevant banking, data, project, and/or leadership role.
Banking experience and knowledge of industry regulatory requirements is preferred.
Risk Management, Information Security, Information Technology, and/or Banking Operations experience is a plus.
Experience in establishing and executing data governance, data quality, or data management practices.
Demonstrated experience collaborating with cross functional teams and ability to develop, recommend, and implement solutions.
Project management experience to include developing and executing project plans and roadmaps.

💡 Responsibilities

Promote the value of the Data Intelligence Program and influence a data-driven culture.
Develop a working knowledge of the Bank’s organizational structure, operations, product and service offering, and data architecture including data sources, data flows, and control points and document where appropriate.
Develop, document, implement, and manage processes supporting data governance, data stewardship, and data quality programs.
Continuously assess and improve data governance processes and practices to adapt to changing business needs and regulatory requirements.
Monitor industry trends and advancements to ensure data practices align with the latest standards and technologies.
Lead Data Communities and oversee data-related efforts/activities through completion.
Work with business lines and/or Data Communities to identify and document critical data elements (CDEs) and respective business rules and thresholds for data quality monitoring.
Work with business lines and/or Data Communities to identify root cause of data quality issues and opportunities for process improvement and implement solutions to resolve or reduce repeated issues; supporting documentation should be developed as appropriate.
Support adoption of the Data Intelligence tools, solutions, and processes.
Elevate data-related issues, risks, and gaps and recommend solutions to the Director of Business Initiatives and/or Data Intelligence Committee.
Develop and execute Data Intelligence awareness and training plans as appropriate.
Assist the Director of Business Initiatives with managing data intelligence use cases and business line onboarding as needed.
Assist the Director of Business Initiatives with development and implementation of a data change management process and supporting documentation.
Support maintenance of the Data Intelligence repository (i.e. SharePoint site) by ensuring relevant artifacts such as program documentation, procedures, and meeting packets for data working groups and/or projects are current and available.
Manage projects, where appropriate, in accordance with the Bank’s established project lifecycle process to include but not limited to developing and executing project plans, roadmaps, schedules, business requirements, and testing strategies.
Prepare reports, materials, and status updates for the Data Intelligence Committee and other meetings and/or ad hoc requests as needed.
Collaborate with the Data Intelligence team to achieve common objectives and complete projects timely.
Partner with IT, Information Security, Risk Management, and Privacy teams, as appropriate, to ensure data governance processes and projects align with standards and/or regulatory requirements of the respective area.
Represent Data Intelligence on committees, projects, and process forums (i.e. ARB, DCAB) as appropriate.
Perform other duties as assigned.

Leadership Project Management SQL Business Intelligence Data Analysis ETL SharePoint Data engineering Data Structures Communication Skills Analytical Skills Collaboration Microsoft Excel Problem Solving Agile methodologies Risk Management Data visualization Data modeling Data analytics Data management Change Management

Posted 2 days ago

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🔥 Senior Golang Engineer

Posted 2 days ago

📍 United States, Canada, Mexico, Europe

🧭 Full-Time

🔍 Software Development

🔧 Requirements

5+ years of experience as a Data Engineer
Snowflake architecture expertise for multi-tenant B2B applications
Performance optimization for customer-facing data models and analytics.
Advanced SQL skills for complex query optimization
Proficiency in Python, Scala, or Go for data pipeline development
Experience analyzing source data structures and recommending improvements
Ability to collaborate with engineering teams on data design
Experience with ETL/ELT pipelines (Airflow, dbt)
Integration experience with Power BI, Tableau, and Sigma
Mentoring skills for report creation using BI tools
Data quality management for customer-facing products
Experience with GitHub/source control and CI/CD pipelines (GitHub Actions or Jenkins)
Understanding of multi-tenant data security and governance

💡 Responsibilities

Develop and enhance AI workflows in support of the various QAD applications.
Complete delivery work committed during the sprint to achieve business goals.
Help the business maintain a competitive edge by leveraging the latest AI technologies.
Provide subject matter expertise during incidents to resolve customer issues quickly.
Participate in forums to explore interests outside of the sprint work and contribute ideas to continuously improve the system.
Commit to the team to help the team and the wider business achieve our goals.
Write testable and maintainable code.

Python SQL ETL Jenkins Snowflake Tableau Airflow API testing Data engineering Go CI/CD RESTful APIs Scala Data modeling

Posted 2 days ago

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🔥 Staff Data Engineer (Remote, United States)

Posted 3 days ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Apollo.io👥 501-1000💰 $100,000,000 Series D over 1 year agoSoftware Development

🔧 Requirements

8+ years of experience as a data platform engineer or a software engineer in data or big data engineer.
Experience in data modeling, data warehousing, APIs, and building data pipelines.
Deep knowledge of databases and data warehousing with an ability to collaborate cross-functionally.
Bachelor's degree in a quantitative field (Physical/Computer Science, Engineering, Mathematics, or Statistics).

💡 Responsibilities

Develop and maintain scalable data pipelines and build new integrations to support continuing increases in data volume and complexity.
Develop and improve Data APIs used in machine learning / AI product offerings
Implement automated monitoring, alerting, self-healing (restartable/graceful failures) features while building the consumption pipelines.
Implement processes and systems to monitor data quality, ensuring production data is always accurate and available.
Write unit/integration tests, contribute to the engineering wiki, and document work.
Define company data models and write jobs to populate data models in our data warehouse.
Work closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.

Python SQL Apache Airflow Apache Hadoop Cloud Computing ETL Apache Kafka Data engineering FastAPI Data modeling Data analytics

Posted 3 days ago

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🔥 Sr. Financial Crimes Systems Tuning Analyst - Remote or Hicksville, NY, or Manhattan, NY or Troy, MI

Posted 3 days ago

📍 United States of America

💸 84878.0 - 140048.77 USD per year

🔍 Financial

🏢 Company: flagstar

🔧 Requirements

Undergraduate Degree in Business or Information Systems, or related field.
3-5 years of financial industry, BSA/AML or related experience.
3-5 years of experience with TM system Tuning & Optimization (ATL/BTL) analysis.
3-5 years of financial institution IT experience.
Microsoft Excel (vlookups, pivot tables, macros), PowerPoint and Word
SQL Server or similar SQL-based database
Python, R Scripting or similar scripting language
Tableau or similar data visualization tool

💡 Responsibilities

Works with FCC team, supporting the workstream with key deliverables and projects, including periodic tuning and optimization and regulatory deliverables of FCC systems.
Performs and documents procedures for data preparation including analysis and interpretation.
Creates and executes a tuning process and ensure that a consistent and repeatable methodology is followed including but not limited to the following:
Enhances rule execution efficiency.
Develops and performs statistical analysis to identify patterns and correlations in the data.
Creates visually compelling and easy-to-understand dashboards and reports adhering to best practices and governance standards.
Communicates findings to stakeholders through charts, graphs, and presentations.
Translates complex data findings into compelling narratives that drive business decisions using both static and dynamic analytic tools.
Gathers and documents business requirements: Works with key stakeholders in FCC department and understand their requirements to arrive at the desired end-state.
Creates analytical data models to support dynamic reporting requirements to meet FCC functional requirements.
Assists in designing and implementing risk-based alert scoring, addressing and resolving logic and configuration in monitoring scenarios.
Actively participates in system upgrades.
Assists in automated solutions to improve process efficiency.
Uses advanced statistical techniques like clustering and regression analysis to ensure appropriate rigor around optimization process.
Adheres to standards for segmentation methodology, scenario tuning methodology, peer grouping, below/above the line (BTL/ATL) sampling methodology.
Configures/executes periodic above the line (ATL) and below the line (BTL) testing for AML rules.
Provides detailed quantitative analysis of the test results.

Python SQL Data Analysis ETL Tableau Microsoft Excel Compliance Reporting Risk Management Data visualization Financial analysis Data modeling Scripting Data management

Posted 3 days ago

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