Millennium

Data Engineer

Software Engineer - Treasury

This Data Engineer role within Millennium's latency-critical trading group involves building and maintaining a low-latency data platform for systematic portfolio engines. Responsibilities include monitoring and analyzing market data quality, identifying and resolving data gaps, documenting exchange microstructure behavior and message timestamp rules, conducting alpha research, building data acquisition tools, collaborating with vendors and portfolio managers, performing data cleaning and transformation, and developing data analysis and visualization tools.  The ideal candidate will possess strong programming skills (Python, C++, SQL), data analysis expertise (R, MatLab, etc.), and a deep understanding of statistical testing methods.  The role requires handling large datasets in a hybrid cloud environment and building high-performance analytical systems.

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 About the job
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 Millennium is a global investment management firm, built on a sophisticated operating system at scale. We seek to pursue a diverse array of investment strategies, and we empower our employees to deliver exceptional outcomes and enable our portfolio managers to do what they do best – navigate the markets. Job Description We are building a world-class systematic data platform which will power the next generation of our systematic portfolio engines. The latency critical trading group is looking for a Data Scientist/Engineer to join our growing team. The team consists of low latency linux engineers, network engineers, datacenter engineers, and C++ engineers who are responsible for building our low latency stack. This is an opportunity for individuals who are passionate about quantitative investing. The role builds individual’s knowledge and skills in four key areas of quantitative investing, namely: data, statistics, technology, and financial markets. Desirable Candidates <ul><li>Ph.D. or master's in computer science, mathematics, statistics, or other field requiring quantitative analysis or equivalent experience</li><li>Three years of financial industry experience</li><li>Experience working with systematic investing teams is a plus</li><li>Programming expertise in Python and C++</li><li>Data analysis experience with R, MatLab, scitoolkit, pytorch, or similar</li><li>Programming skills in SQL</li><li>Strong problem-solving skills</li><li>Effective communication skills</li><li>Strong understanding of modern statistical testing methods </li></ul>
Job Responsibilities <ul><li>Monitoring and Analysis</li> <ul><li>Accessing quality of all captured market data - both live and historical</li><li>Inventorying all gaps and handling closing gaps via multiple techniques (other internal captures, vendor data, exchange data, etc)</li><li>Extending parsing and identification of other gaps </li><li>Understanding and Documenting session times including holiday schedules</li><li>Comparing day-on-day changes in latency, data rate, bursts, etc</li></ul>
<li>Research</li> <ul><li>Documenting history of exchange microstructure behavior changes</li><li>Understanding and Documenting message timestamp rules for each exchange</li><li>Documenting history of session schedule changes and protocols</li><li>Alpha research and presentation to portfolio managers and trading teams</li><li>Building technology tools to acquire and tag datasets</li><li>Engaging with vendors, brokers to understand characteristics of datasets</li><li>Interacting with portfolio managers and quantitative analysts to understand their use cases</li><li>Building exchange microstructure expertise and helping educate clients as needed</li><li>Analyzing datasets to generate key descriptive statistics</li><li>Cleaning historical data</li><li>Utilizing and maintaining world-class data processing and transformation techniques</li></ul>
<li>Tools</li> <ul><li>Building data analysis tools on top of our captured data</li><li>Improving data visualization tools and capabilities</li></ul>
<li>Technical</li> <ul><li>Consolidating several PCAPs in a single PCAPNG with meta-data to represent capture location/time across capture regions</li><li>Assessing PTP (Precision Time Protocol) quality within a sole source and across multiple Manage large data sets in a hybrid multi-cloud/on-prem sources environment</li><li>Build performant systems able to analyze terabytes of data quickly </li></ul>
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Enhance firm C++ analytics and expose them in a python environment
 
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<div class="ats-description">
 <h4>Job Summary:</h4> 
 <div class="additional-field-value-razor"><h2>Disney Entertainment &amp; ESPN Product &amp; Technology</h2>On any given day at Disney Entertainment &amp; ESPN Product &amp; Technology (DEEP&amp;T), we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.The Product &amp; Data Engineering team is responsible for end to end development for Disney’s world-class consumer-facing products, including streaming platforms Disney+, Hulu, and ESPN+, and digital products &amp; experiences across ESPN, Marvel, Disney Studios, NatGeo, and ABC News. The team drives innovation at scale for millions of consumers around the world across Apple, Android, Smart TVs, game consoles, and the web, with our platforms powering core experiences like personalization, search, messaging and data.A few reasons why we think you’d love working for Disney Entertainment &amp; ESPN Technology<ul><li>Building the future of Disney’s media business: DE&amp;E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.</li><li>Reach &amp; Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.</li><li>Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment &amp; news.</li></ul>This role involves building and maintaining our Identity and Device Data products.&nbsp; These products serve as a comprehensive source of truth for customer identifiers and their devices. The role requires senior-level knowledge of building scalable, fault-tolerant data processing pipelines and backend to ensure the reliable delivery of both real-time and batch data.<h2>Responsibilities</h2><ul><li>Build and maintain product-driven initiatives to improve and expand Identity and Device data product offerings</li><li>Enhance/redesign existing data models with input from Architecture in order to modernize products and/or improve performance and efficiency. Enhance/improve the underlying codebase to be extensible, reusable, and maintainable. Participate in code reviews and as well as on-call support roster.</li><li>Promote and support Agile methodologies such as Scrum, and Kanban by actively participating in regular ceremonies such as stand-up, retrospectives and sprint planning.</li><li>Collaborate with your squad, Product Managers, Designers, QA, Operations, and other stakeholders to understand requirements and articulate technical decisions and outcomes.</li><li>Serve as a senior resource to other Data Engineers on the team, and mentor junior members of the team helping to improve their skills, knowledge, and productivity.</li></ul><h2>Basic Qualifications</h2><ul><li>5+ years of related big data engineering experience modeling and developing large data pipelines</li><li>Hands-on experience with distributed systems such as Hadoop or Databricks compute using tools/libraries such as Spark, Presto, Hive to query and process large datasets at the petabyte level.</li><li>Strong Python, Scala and SQL skills processing big datasets</li><li>Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, Big Query, Databricks)</li><li>Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices</li><li>Operational experience in multi-system/services production environment as senior data engineer and point-of-contact / SME</li><li>Problem solving skills with strong attention to detail and excellent analytical and communication skills</li><li>Solid experience with data integration and orchestration toolsets (e.g. Airflow), CI/CD</li><li>Solid experience with AWS S3</li></ul><h2>Preferred Qualifications </h2><ul><li>Demonstrated ability with cloud infrastructure technologies, including Terraform</li><li>Experience with:&nbsp;Snowflake, Databricks, Airflow, AWS &nbsp;</li></ul><h2>Required Education</h2><ul><li>Bachelor's degree in Computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.&nbsp;</li></ul><h2>Additional Information</h2>#DISNEYTECH The hiring range for this position in Santa Monica, CA is $138,900 to $186,200 per year, in Seattle, WA is $145,400 to $195,000 per year, and in New York, NY is $145,400 to $195,000 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.</div>
 
 
 
 
 
 
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