Role Description We are seeking a Senior Data Engineer. Qualifications - 5+ years of experience in data analysis or data engineering - 3+ years of hands-on experience building and supporting production ETL/ELT pipelines - Advanced SQL skills (CTEs, window functions, performance optimization) - Strong Python skills (pandas, API integrations) - Proven experience with Snowflake (schema design, Snowpipe, Streams, Tasks, performance tuning, data quality) - Solid knowledge of AWS services: S3, Lambda, EventBridge, IAM, CloudWatch, Step Functions - Strong understanding of dimensional data modeling (Kimball methodology, SCDs) - Experience working with enterprise systems (ERP, CRM, or similar) Requirements - Experience with data quality frameworks (Great Expectations, Deequ) - Knowledge of CDC tools and concepts (AWS DMS, Kafka, Debezium) - Hands-on experience with data lake technologies (Apache Iceberg, Parquet) - Exposure to ML data pipelines and feature stores (SageMaker Feature Store) - Experience with document processing tools such as Amazon Textract Core Responsibilities - Design and develop ETL/ELT pipelines using Snowflake, Snowpipe, internal systems, Salesforce, SharePoint, and DocuSign - Build and maintain dimensional data models in Snowflake using dbt, including data quality checks (Great Expectations, Deequ) - Implement CDC patterns for near real-time data synchronization - Manage and evolve the data platform across S3 Data Lake (Apache Iceberg) and Snowflake data warehouse - Build and maintain Medallion architecture data lake in Snowflake - Prepare ML features using SageMaker Feature Store - Develop analytical dashboards and reports in Power BI Benefits - Continuous learning and career growth opportunities - Professional training and English/Spanish language classes - Comprehensive medical insurance - Mental health support - Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more - Flexible working hours - Inclusive and supportive culture Company Description Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world. Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture. Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics.

Overview Position Summary: We’re looking for an Analytics Engineer II to build our next-generation enterprise metrics store and enable insights across underwriting, sales, product, claim and experience. This role blends analytics engineering and prompt engineering, supporting our journey toward a fully governed, AI-ready data ecosystem.As an Analytics Engineer, you will sit at the intersection of:• data modeling (dbt, semantic layer)• business metrics (insurance domain: quotes, binds, premium, agency performance)• analytics engineering (root cause analysis, metric relationships, metric store)This is a hands-on role where you will design, build, and scale core metrics and analytical workflows, working closely with product, business, and engineering stakeholders. The team is evolving toward exposing metric infrastructure as internal services, so you’ll have the opportunity to shape that API layer as it matures. Geo-Salary Information An in-person interview may be required during the hiring process State specific pay scales for this role are as follows: $94,458 to $179,048 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA) $X85,871 to $162,771 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME) $77,283 to $146,494 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV) The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location. Responsibilities Essential Job Functions: - Build and scale the metric layer - Develop and maintain dbt models - Contribute to semantic layer definitions (metrics, dimensions, relationships)Ensure consistency and correctness of: key business metrics o metric hierarchies (metric pyramid) - Implement analytical logic (root cause analysis & metric insights) - Build root cause analysis workflows:Implement baseline comparisons , companion metric analysis - Translate business questions into scalable analytical patterns - Enable metric consumption across toolsSupport metric usage in different BI or analytical tools - Build reusable logic that avoids duplication across tools - Prepare for future API-based metric serving layer - Partner with business and product stakeholders - Work closely with sales, product, underwriting, claims, experience and other business teams, Translate ambiguous questions into: - Structured metrics - Actionable insights - Improve data quality and governance - Define and enforce: - Metric definitions - Dimension standards - Data contracts - Debug issues across: - Upstream pipelines - Semantic layer - Analytical outputs Qualifications Education: - 3–5 years of analytics engineering or similar analytical role experience with dbt or similar transformation frameworks proficiency: models, tests, incremental materialization, Jinja macros - Advanced SQL on a columnar warehouse (Redshift, Snowflake, or BigQuery) - Python for data transformation and analysis (pandas, basic scripting) - Comfort working with YAML-based configuration and version-controlled analytics workflows - Clear written and verbal communication—able to explain metric definitions and data lineage to non-technical stakeholders - Nice to haveP&C insurance domain experienceExperience with:Cohort analysisFunnel metricsPerformance analysisFamiliarity with MetricFlow specifically and the dbt Semantic LayerExposure to Retool or similar low-code tools for operational write-back workflowsFastAPI or similar Python API frameworks (Flask, Django REST) for serving data products as services About the Company Why choose a career at Mercury? At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it. Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life. We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals. Learn more about us here: https://www.mercuryinsurance.com/about/careers Perks and Benefits We offer many great benefits, including: - Competitive compensation - Flexibility to work from anywhere in the United States for most positions - Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours) - Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus) - Medical, dental, vision, life, and pet insurance - 401 (k) retirement savings plan with company match - Engaging work environment - Promotional opportunities - Education assistance - Professional and personal development opportunities - Company recognition program - Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more Mercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law. Pay Range USD $94,458.00 - USD $179,048.00 /Yr.

Role Description APAC Strategy and Operations Specialist - Agency Partner Scope of Services and Deliverables for APAC YouTube Social Duration: 6 months (FTC) Location: Mumbai, India (Remote) Work Shift: Early Morning Start hours basis SGT timezone YouTube has seen tremendous growth in APAC. Millions of users use YouTube to enjoy a diverse range of content produced by a dynamic and vibrant creator and partner ecosystem. The scope outlines the Strategy and Operations services required for the YouTube APAC Social team. This scope requires close collaboration with various cross-functional teams Globally. Hence, we're looking for someone with strong project management and communication skills, who thinks analytically and has a bias for operations and execution. Having a strong understanding of cultural nuances and a passion for social and video culture would help as well. While this scope is within the APAC Social Marketing Team and requires understanding of marketing, social and media, it is not an editorial, community or campaign management scope, although this experience would be beneficial. Candidates for this scope could have worked as: - An associate in digital consulting - A digital or social marketing manager in technology, media or entertainment - A strategic account manager or project director in a social, digital or PR agency What you will be doing: - Strategic Planning & Reporting (OKRs & QBRs) - Manage Team OKRs: Manage the team’s Objectives and Key Results (OKRs), ensuring tracking against goals and establishing a rigorous process to adhere to aligned OKR measurement methodologies. Ensures OKRs are aligned, well measured, reviewed monthly/quarterly, and published to key stakeholders with meaningful commentary. - Quarterly Business Reviews (QBRs): Manage QBRs with leadership and the social team, ensuring that all activities are captured, elevated, and presented in a comprehensive manner. - Team Operations & Enablement: - Team Communication Lead: Act as the lead for internal team communications, including the creation of newsletters and developing an efficient operating model within the Social team as required. - Budget Operations: Oversee budget monitoring and vendor management, ensuring Purchase Orders (POs) are raised, spending is accurately forecasted, and Statements of Work (SOWs) are processed on time. - Process Excellence: Ensure the excellence of key internal operational processes and drive continuous process optimization. Conduct training for the teams as needed. - Real-time optimisation: Work with analysts to create dashboards on social media performance indicators and reports as needed. This is a specialist (vendor) scope embedded with the extended YouTube APAC Social Marketing Team and will work directly with the APAC Social Marketing Lead on your assignments. Qualifications - Strong written and oral communication skills - Advanced Spreadsheet user, including basic automation - Native in Japanese, Korean or Hindi - Experience in social analytics and knowledge of social media monitoring and listening tools (such as BrandWatch, Sprinklr) is a plus - Experience in working with statistical analysis and data mining software is a plus - Passion for and inquisitive about AI and new technologies - Understanding and knowledge of AI tools is beneficial, but ability to learn and digest benefits and features of AI tools is critical Requirements - Req ID: 16963 - #LI-AS2 - #LI-Remote Benefits - Equal opportunity employer committed to creating an inclusive working environment - Encouragement for all employees to reach their full potential - Valuing and respecting individual differences - Consideration for employment without regard to protected characteristics - Ambitious environmental goals around sustainability - Science-based emissions reduction targets - Embedding sustainability into every department and through every stage of the project lifecycle

Role Description - Liderar o design e a evolução de pipelines de dados em ambiente cloud (AWS); - Conduzir a migração de soluções de dados de Azure para AWS; - Definir e implementar arquiteturas modernas (Lakehouse, Data Lakes); - Garantir eficiência, escalabilidade e governança dos dados (catalog, lineage, compliance); - Orquestrar pipelines robustos e sustentáveis em produção; - Estruturar ambientes com CI/CD e boas práticas de engenharia; - Apoiar iniciativas de dados para Machine Learning; - Atuar como referência técnica, propondo melhorias e direcionamentos. Qualifications - Experiência sólida como Engenheiro(a) de Dados Sênior; - Forte domínio em Python, Spark (PySpark) e SQL; - Experiência com orquestração (Airflow, Step Functions ou ADF); - Vivência com Data Lakes e arquitetura Lakehouse (Delta, Iceberg, Parquet); - Experiência com AWS (EMR, Glue, Lake Formation); - Conhecimento em Azure (Data Factory, Synapse, entre outros); - Experiência com bancos como Redshift, Snowflake, PostgreSQL; - Prática com CI/CD (Terraform, GitHub Actions, CloudFormation); Requirements - Diferenciais: Experiência em migração entre clouds (Azure → AWS); - Atuação com dados para Machine Learning; - Vivência em ambientes de alta escala.