Senior Platform Data Engineer

Elios Talent is seeking a Senior Platform Data Engineer to support a high-visibility, year-long platform transformation initiative. This role focuses on building and operating a centralized, enterprise-grade data platform, requiring end-to-end ownership of design, build, test, deploy, monitor, and continuous improvement of data models and pipelines.

Responsibilities:

• Build and maintain ingestion pipelines from raw Bronze landing through curated Gold domain models
• Develop transformation models using dbt with testing, Slim CI, and exposure tracking
• Author and manage production-grade Airflow DAGs with SLA monitoring and backfill strategies
• Design and implement streaming and event-driven pipelines (Kafka, Glue Streaming, Delta Live Tables)
• Collaborate with data scientists, platform engineers, and product teams to ship reliable data products
• Implement data quality frameworks and enforce governance standards
• Containerize workloads and deploy to Kubernetes (EKS)
• Contribute to infrastructure as code (Terraform provisioning for S3, IAM, Glue, etc.)
• Document lineage, metadata, ownership, and sensitivity classification

Requirements:

• Bachelor's degree or equivalent experience
• 5–8+ years of experience developing data products and platforms
• Strong background in Agile software development
• Demonstrated success in prior engineering roles
• Strong analytical and problem-solving capabilities
• Python production-level standards (type hints, Pydantic, pytest, Ruff, mypy)
• SQL advanced analytical queries, window functions, optimization
• Experience with Redshift, Snowflake, or Databricks SQL
• dbt Gold-layer modeling and testing
• Slim CI, exposures, meta configurations
• Apache Airflow (DAG authoring, task dependencies, SLAs, backfills)
• Kafka topic consumption
• Hands-on with at least one Cloud Data Platform (Databricks, AWS)
• Data Quality frameworks (Great Expectations, dbt tests, or equivalent)
• Docker & Kubernetes containerized jobs
• Terraform familiarity
• Data Modeling (Dimensional modeling, Slowly Changing Dimensions, Medallion architecture design)
• Experience with Prefect or Dagster
• Financial or time-series modeling experience
• SaaS ingestion via Fivetran, Airbyte, or custom connectors (REST, SFTP, JDBC)
• Change Data Capture (Debezium or connector-based CDC modes)
• Handling semi-structured and unstructured data (PDF, Excel, JSON)
• Designing Bronze schemas for fidelity and downstream flexibility
• Vector embedding pipelines (chunking strategies, embeddings, pgvector/OpenSearch)
• Data lineage tooling (OpenLineage, DataHub, Unity Catalog)
• Governance standards: PII handling, sensitivity classification, column masking, partition-level access
• Migration of legacy data assets (Excel, Access, shared drives)
• ML feature engineering and point-in-time correct pipelines
• Exposure to financial reporting, chart of accounts normalization, or diligence data
• Experience in private equity, investment banking, asset management, or professional services
• Open-source data tooling contributions