<p><strong>Data Modeling and Analysis</strong></p><ul><li>Design data models and optimize performance: Creating the structure of data relationships ensuring efficient data retrieval and calculations.</li><li>Create calculated columns and measures: Using DAX to calculate derived values and aggregate metrics.</li><li>Perform exploratory data analysis (EDA): Using BI tools to explore data, identify trends, and patterns.</li><li>Apply advanced data analysis techniques (e.g., statistical analysis, time series analysis, predictive modeling).</li><li>Integrate machine learning models into Power BI dashboards.</li><li>Experience building semantic models</li></ul><p><strong>Dashboard Development and Visualization</strong></p><ul><li>Designing dashboards: Creating visually appealing and interactive dashboards.</li><li>Creating visualizations: Using charts, graphs, and other visual elements to represent data.</li><li>Implementing interactivity: Adding filters, slicers, and drill-down capabilities.</li><li>Expertise in SQL and DAX and knowledge of Python, R.</li><li>Strong proficiency in Power BI.</li><li>Data modeling and visualization skills.</li><li>Strong problem-solving skills to address technical challenges and data quality issues.</li><li>Analytical skills with capacity to analyze complex data problems and draw meaningful insights.</li></ul>
<p>I’m building a world-class team to power our next generation of data products. We’re looking for a Senior Data Engineer who knows AWS inside and out—someone who can <strong>design secure, scalable data pipelines</strong>, <strong>own ETL/ELT workflows</strong>, <strong>engineer cloud data infrastructure</strong>, and <strong>deliver dimensional and semantic models</strong> that our analysts, data scientists, and applications can trust.</p><p>You’ll work closely with product, security, platform engineering, and analytics to move our architecture toward a <strong>real-time, governed, cost-aware</strong>, and <strong>highly automated</strong> data ecosystem.</p><p><strong>What You’ll Do</strong></p><ul><li><strong>Design & build end-to-end pipelines</strong> on AWS (batch and streaming) using services like <strong>Glue, EMR, Lambda, Step Functions, Kinesis, MSK</strong>, and <strong>Fargate</strong>.</li><li><strong>Develop robust ETL/ELT</strong> (PySpark, Spark SQL, SQL, Python) for structured, semi-structured, and unstructured data at scale.</li><li><strong>Own data storage & processing layers</strong>: <strong>S3 (Lake/Lakehouse), Redshift (or Snowflake on AWS), DynamoDB</strong>, and <strong>Athena</strong> with strong partitioning, compaction, and performance tuning.</li><li><strong>Implement data models</strong> (3NF, dimensional/star, Data Vault, Lakehouse medallion) for analytics and operational workloads.</li><li><strong>Engineer secure infrastructure-as-code</strong> with <strong>Terraform</strong> (or <strong>CDK</strong>) across multi-account setups; implement CI/CD via <strong>GitHub Actions</strong> or <strong>AWS CodeBuild/CodePipeline</strong>.</li><li><strong>Harden security & governance</strong>: use <strong>IAM</strong>, <strong>Lake Formation</strong>, <strong>KMS</strong>, <strong>Secrets Manager</strong>, <strong>VPC/PrivateLink</strong>, <strong>GLUE Catalog</strong>, and fine-grained access controls. Partner with SecOps on compliance (e.g., <strong>SOC 2</strong>, <strong>FedRAMP</strong>, <strong>HIPAA</strong> depending on dataset).</li><li><strong>Observability & reliability</strong>: build monitoring with <strong>CloudWatch</strong>, <strong>OpenTelemetry</strong>, and data quality checks (e.g., <strong>Great Expectations</strong>, <strong>Deequ</strong>), implement SLOs and alerts.</li><li><strong>Champion best practices</strong>: code reviews, testing (unit/integration), documentation, runbooks, and blameless postmortems.</li><li><strong>Mentor</strong> mid-level engineers and collaborate on architectural decisions, standards, and technical roadmaps.</li></ul><p><br></p>