{"schemaVersion":"jobsearcher.job.v1","id":"00aaea2cc1e325a76120eeee","url":"https://jobsearcher.com/jobs/00aaea2cc1e325a76120eeee","canonicalUrl":"https://jobsearcher.com/jobs/00aaea2cc1e325a76120eeee","title":"Data Analytics Engineer","description":"Job Description: We are seeking an experienced Data Analytics Engineer to design, build, and optimize scalable data pipelines and analytics infrastructure that power critical financial products and decisions. You will work at the intersection of software engineering and data analytics — building reliable ETL/ELT pipelines, orchestrating cloud-native workflows, and enabling trusted, high-quality data for reporting, risk, and product teams. This role requires strong engineering discipline (version control, CI/CD, infrastructure-as-code) combined with deep SQL and PySpark expertise, ideally within a regulated banking or financial services environment.\n\nResponsibilities: Design, build, and maintain scalable, reliable ETL/ELT data pipelines across cloud and on-prem sources, ensuring data quality, lineage, and auditability.\nDevelop and optimize Python/ PySpark and SQL-based data transformations for large-scale, high-volume financial datasets.\nArchitect and manage data pipeline orchestration (e.g., Airflow, Databricks Workflows, Step Functions) to automate ingestion, transformation, and delivery.\nBuild and maintain CI/CD pipelines using GitHub/GitHub Actions to support automated testing, deployment, and version-controlled infrastructure changes.\nDevelop cloud-based solutions on AWS (S3, Glue, EMR, Redshift, Lambda, IAM) supporting analytics, reporting, and downstream ML use cases.\nDeploy and manage infrastructure and pipelines as code, following best practices for environment promotion, rollback, and monitoring.\nMonitor, troubleshoot, and optimize pipeline performance, query efficiency, and cost across the data stack.\nPartner with data scientists, analysts, product, and risk/compliance teams to translate business requirements into robust data solutions.\nEnforce data governance, security, and regulatory compliance standards appropriate for financial data (PII, SOX, PCI, etc.).\nDocument pipeline architecture, data models, and processes; contribute to engineering standards and code review practices.\n\nQualifications: Required Technical Skills\nAdvanced proficiency in Python for scripting, automation, and data engineering workflows.\nStrong hands-on experience with PySpark for distributed data processing at scale.\nExpert-level SQL and Advanced SQL (window functions, query optimization, complex joins, performance tuning).\nSolid experience with AWS cloud services and cloud-based application/data development (S3, Glue, EMR, Redshift, Lambda, IAM, CloudWatch).\nProven expertise building and orchestrating data pipelines (Airflow, Databricks Workflows, Step Functions, or equivalent).\nHands-on CI/CD experience using GitHub / GitHub Actions for automated build, test, and deployment.\nDeep understanding of ETL/ELT design patterns, data modeling, and data warehousing concepts.\nExperience deploying infrastructure and pipelines via code (e.g. version-controlled deployments).\nDemonstrated ability to optimize pipeline performance, query execution, and cloud resource/cost efficiency.\nPreferred / Desired Skills (Nice to Have)\nHands-on experience with Databricks (Delta Lake, Unity Catalog, notebooks, cluster optimization).\nFamiliarity with Terraform or CloudFormation for infrastructure as code.\nExperience with streaming data technologies (Kafka, Kinesis, Spark Structured Streaming).\nExposure to data quality/testing frameworks (Great Expectations, Dbt tests).\nKnowledge of Dbt for transformation and analytics engineering workflows.\nUnderstanding of financial data domains — payments, lending, risk, fraud, or accounting data.\nRelevant certifications (AWS Certified Data Analytics/Solutions Architect, Databricks Certified Data Engineer).\nQualifications\nBachelor’s degree in computer science, Engineering, Data Science, or a related field (or equivalent practical experience).\n5+ years of experience in data engineering, analytics engineering, or a related technical role.\nPrior experience working within banking, fintech, or financial services, with awareness of regulatory and data-security requirements.\nDemonstrated track record delivering production-grade data pipelines in a cloud environment.\n\nSoft Skills\nStrong analytical and problem-solving skills with attention to detail and data accuracy.\nExcellent communication skills; able to translate technical concepts for non-technical stakeholders.\nCollaborative mindset with experience working cross-functionally with analysts, engineers, and business teams.\nSelf-directed and comfortable owning projects end-to-end in a fast-paced, regulated environment.\nStrong ownership mentality around data quality, reliability, and documentation.\nBase Compensation Range: $140,000- $155,000\nThe posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.","company":"Ex","rawCompany":"ex","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-11T16:08:52.620Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Analytics Engineer","description":"Job Description: We are seeking an experienced Data Analytics Engineer to design, build, and optimize scalable data pipelines and analytics infrastructure that power critical financial products and decisions. You will work at the intersection of software engineering and data analytics — building reliable ETL/ELT pipelines, orchestrating cloud-native workflows, and enabling trusted, high-quality data for reporting, risk, and product teams. This role requires strong engineering discipline (version control, CI/CD, infrastructure-as-code) combined with deep SQL and PySpark expertise, ideally within a regulated banking or financial services environment.\n\nResponsibilities: Design, build, and maintain scalable, reliable ETL/ELT data pipelines across cloud and on-prem sources, ensuring data quality, lineage, and auditability.\nDevelop and optimize Python/ PySpark and SQL-based data transformations for large-scale, high-volume financial datasets.\nArchitect and manage data pipeline orchestration (e.g., Airflow, Databricks Workflows, Step Functions) to automate ingestion, transformation, and delivery.\nBuild and maintain CI/CD pipelines using GitHub/GitHub Actions to support automated testing, deployment, and version-controlled infrastructure changes.\nDevelop cloud-based solutions on AWS (S3, Glue, EMR, Redshift, Lambda, IAM) supporting analytics, reporting, and downstream ML use cases.\nDeploy and manage infrastructure and pipelines as code, following best practices for environment promotion, rollback, and monitoring.\nMonitor, troubleshoot, and optimize pipeline performance, query efficiency, and cost across the data stack.\nPartner with data scientists, analysts, product, and risk/compliance teams to translate business requirements into robust data solutions.\nEnforce data governance, security, and regulatory compliance standards appropriate for financial data (PII, SOX, PCI, etc.).\nDocument pipeline architecture, data models, and processes; contribute to engineering standards and code review practices.\n\nQualifications: Required Technical Skills\nAdvanced proficiency in Python for scripting, automation, and data engineering workflows.\nStrong hands-on experience with PySpark for distributed data processing at scale.\nExpert-level SQL and Advanced SQL (window functions, query optimization, complex joins, performance tuning).\nSolid experience with AWS cloud services and cloud-based application/data development (S3, Glue, EMR, Redshift, Lambda, IAM, CloudWatch).\nProven expertise building and orchestrating data pipelines (Airflow, Databricks Workflows, Step Functions, or equivalent).\nHands-on CI/CD experience using GitHub / GitHub Actions for automated build, test, and deployment.\nDeep understanding of ETL/ELT design patterns, data modeling, and data warehousing concepts.\nExperience deploying infrastructure and pipelines via code (e.g. version-controlled deployments).\nDemonstrated ability to optimize pipeline performance, query execution, and cloud resource/cost efficiency.\nPreferred / Desired Skills (Nice to Have)\nHands-on experience with Databricks (Delta Lake, Unity Catalog, notebooks, cluster optimization).\nFamiliarity with Terraform or CloudFormation for infrastructure as code.\nExperience with streaming data technologies (Kafka, Kinesis, Spark Structured Streaming).\nExposure to data quality/testing frameworks (Great Expectations, Dbt tests).\nKnowledge of Dbt for transformation and analytics engineering workflows.\nUnderstanding of financial data domains — payments, lending, risk, fraud, or accounting data.\nRelevant certifications (AWS Certified Data Analytics/Solutions Architect, Databricks Certified Data Engineer).\nQualifications\nBachelor’s degree in computer science, Engineering, Data Science, or a related field (or equivalent practical experience).\n5+ years of experience in data engineering, analytics engineering, or a related technical role.\nPrior experience working within banking, fintech, or financial services, with awareness of regulatory and data-security requirements.\nDemonstrated track record delivering production-grade data pipelines in a cloud environment.\n\nSoft Skills\nStrong analytical and problem-solving skills with attention to detail and data accuracy.\nExcellent communication skills; able to translate technical concepts for non-technical stakeholders.\nCollaborative mindset with experience working cross-functionally with analysts, engineers, and business teams.\nSelf-directed and comfortable owning projects end-to-end in a fast-paced, regulated environment.\nStrong ownership mentality around data quality, reliability, and documentation.\nBase Compensation Range: $140,000- $155,000\nThe posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.","datePosted":"2026-08-11T16:08:52.620Z","dateModified":"2026-08-11T16:08:52.620Z","hiringOrganization":{"@type":"Organization","name":"Ex","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"00aaea2cc1e325a76120eeee"},"url":"https://jobsearcher.com/jobs/00aaea2cc1e325a76120eeee"}}