Data Engineer

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    "ExternalDescriptionStr": "<p><strong><u>Innovation Hub Overview</u></strong></p>\n<p>Jefferies is creating a Technology Innovation Hub in Pune, a greenfield opportunity to build the systems that power global markets. As our first India technology center, this hub brings together hands&nbsp;on builders who engineer the platforms behind Jefferies’ growth across capital markets, investment banking, and institutional securities.&nbsp;We’re&nbsp;scaling toward an elite team of 500 engineers while&nbsp;maintaining&nbsp;the agility, ownership, and meritocratic spirit that defines Jefferies. From cloud and data to AI, risk, and core business technologies, teams in Pune&nbsp;will&nbsp;lead&nbsp;high&nbsp;impact work with a global mandate.</p>\n<p><strong><u>IT Corporate Technology&nbsp;</u></strong></p>\n<p>Corporate Technology powers Jefferies’ enterprise operations, enabling front-, middle-, and back-office teams to run efficiently, securely, and in compliance at scale. The group delivers and supports integrated platforms across HR, Finance, Compliance &amp; Legal, Treasury, Client Onboarding, Operations, Centralized Data Services, Regulatory Reporting, Loan Operations, and FX Trading, while also leading firmwide digitalization initiatives focused on automation and process efficiency.</p>\n<p>The team uses&nbsp;modern&nbsp;technology&nbsp;stack—including AWS and Azure, Snowflake, Qlik Sense, and best-in-class vendor solutions—to build next-generation capabilities in AI/ML, enterprise analytics, and process automation (RPA and low-code/no-code). Roles in Corporate Technology offer hands-on work with cloud, data, and automation platforms, close collaboration with engineers, product managers, and business stakeholders, and end-to-end exposure to how a global financial services firm&nbsp;operates</p>\n<p><strong>Job Summary</strong></p>\n<p>We are seeking a skilled and detail-oriented <strong>Data Engineer</strong> to join our cross-functional Agile team. In this role, you will be responsible for designing, building, and maintaining modular, reliable data transformation pipelines using <strong>dbt (Data Build Tool)</strong> in a <strong>Snowflake</strong> environment. You will collaborate closely with backend and frontend engineers, product managers, and analysts to create analytics-ready data models that power application features, reporting, and strategic insights. This is an exciting opportunity for someone who values clean data design, modern tooling, and working at the intersection of engineering and business.</p>\n<p><strong>Key Responsibilities</strong></p>\n<ul>\n <li>Design, build, and maintain scalable, modular <strong>dbt</strong> models and transformation pipelines using DBT Core.</li>\n <li>Understand DBT Architecture thoroughly and experience in writing Python operators in DBT flow. Strong experience in writing Jinja code, macros, seeds etc.</li>\n <li>Design and develop data warehouses using <strong>Snowflake.</strong></li>\n <li>Build and maintain <strong>ETL/ELT pipelines</strong> to load data from multiple sources.</li>\n <li>Optimize <strong>Snowflake performance</strong> (Clustering, Warehouses, Query tuning).</li>\n <li>Implement <strong>data security</strong> (roles, access control, masking)</li>\n <li>Knowledge of <strong>data modeling</strong> techniques like data vault and dimensional modeling (Kimball/Inmon).</li>\n <li>Automate workflows using data orchestration tools (<strong>Apache Airflow or Snowflake Tasks</strong>)</li>\n <li>Collaborate with full-stack developers and UI/UX engineers to support application features that rely on transformed datasets.</li>\n <li>Work closely with analysts and stakeholders to gather data requirements and translate them into reliable data models.</li>\n <li>Enforce data quality through rigorous testing, documentation, and version control in dbt.</li>\n <li>Participate in Agile ceremonies (e.g., stand-ups, sprint planning) and manage tasks using <strong>Jira</strong>.</li>\n <li>Integrate dbt into <strong>CI/CD pipelines</strong> and support automated deployment practices.</li>\n <li>Monitor data performance and pipeline reliability, and proactively resolve issues.</li>\n</ul>\n<p><strong>Mandatory Qualifications &amp; Skills</strong></p>\n<ul>\n <li><strong>6-11 years</strong> of experience in <strong>data engineering</strong> or <strong>analytics engineering</strong>, with a focus on SQL-based data transformation.</li>\n <li>Hands-on production experience using <strong>dbt core or dbt cloud</strong> as a primary development tool.</li>\n <li>Strong command of <strong>SQL</strong> and solid understanding of data modeling best practices (e.g., star/snowflake schema).</li>\n <li>Proven experience with <strong>Snowflake</strong> as a cloud data warehouse.</li>\n <li>Python skills for data pipeline integration or ingestion.</li>\n <li>Familiarity with <strong>Git-based version control</strong> workflows.</li>\n <li>Strong communication and collaboration skills, with the ability to work across engineering and business teams.</li>\n <li>Experience working in <strong>Agile/Scrum</strong> environments and managing work using <strong>Jira</strong>.</li>\n</ul>\n<p><strong>Nice-to-Have Skills</strong></p>\n<ul>\n <li>Exposure to <strong>CI/CD pipelines</strong> and integrating dbt into automated workflows.</li>\n <li>Experience with <strong>cloud platforms</strong> such as <strong>AWS</strong>.</li>\n <li>Understanding of how data is consumed in downstream analytics tools (e.g., <strong>Sigma</strong>, <strong>Qlik</strong>, <strong>Power BI</strong>).</li>\n <li>Familiarity with <strong>Docker</strong> and container-based development.</li>\n</ul>\n<p><strong>Education &amp; Experience</strong></p>\n<ul>\n <li>Bachelor’s degree in computer science, Data Engineering, or related field.</li>\n <li>A track record of building and maintaining scalable dbt projects in a production setting with Snowflake and Airflow.</li>\n <li>Experience working in cross-functional teams involving developers, analysts, and product managers.</li>\n <li>A strong sense of ownership, documentation habits, and attention to data quality and performance.</li>\n</ul>\n<p>#LI-JM1</p>",
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    "CorporateDescriptionStr": "<p class=\"MsoNormal\"></p>\n<p class=\"MsoNormal\">Jefferies is a leading global, full-service investment banking and capital markets firm that provides advisory, sales and trading, research, and wealth and asset management services. With more than 40 offices around the world, we offer insights and expertise to investors, companies, and governments.</p>\n<p class=\"MsoNormal\">At Jefferies, we believe that diversity fosters creativity, innovation and thought leadership through the infusion of new ideas and perspectives. We have made a commitment to building a culture that provides opportunities for all employees regardless of our differences and supports a workforce that is reflective of the communities where we work and live. As a result, we are able to pool our collective insights and intelligence to provide fresh and innovative thinking for our clients.</p>\n<p class=\"MsoNormal\">Jefferies is an equal employment opportunity&nbsp;employer, and takes affirmative action to ensure that all qualified applicants&nbsp;will receive consideration for employment without regard to&nbsp;race,&nbsp;creed, color, national origin, ancestry,&nbsp;religion, gender, pregnancy,&nbsp;age, physical&nbsp;or mental disability, marital status, sexual orientation, gender identity or expression, veteran or military status, genetic information, reproductive health decisions, or any other factor protected by applicable law. We are committed to hiring the most qualified applicants and&nbsp;complying with&nbsp;all federal, state, and local equal employment opportunity laws. As part of this commitment, Jefferies will extend reasonable&nbsp;accommodations&nbsp;to individuals with disabilities, as&nbsp;required by&nbsp;applicable law.</p>",
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