Senior Data Engineer: Financial Data Pipelines & Cloud

D.A. Davidson; Oregon; On-site; USD 74,000 - 118,000; Full time

Benefits offered by this job

Medical, Dental and Vision

401(k) and ESOP contribution

Vacation and sick leave

Paid holidays

Professional Development Opportunities

Tuition Reimbursement ($15,000)

Discounted personal insurance

Charitable gift-matching

Davidson Day of Giving

Job summary

D.A. Davidson Companies is seeking a Data Engineer to expand and optimize data pipeline architecture, monitor and troubleshoot data flows, and deliver secure data provisioning. You will collaborate with software teams, DBAs, data analysts and end users on complex data initiatives to ensure best-practice delivery.

The role emphasizes building scalable pipelines, maintaining data quality, and supporting data-related technical issues for stakeholders across the firm.

Qualifications

• 5+ years of Data Engineering experience in an oversight capacity.
• Extensive domain-specific experience in the Financial Services industry.
• Experience with Microsoft cloud-based technologies in a hybrid architecture.
• Advanced working TSQL knowledge and experience with relational databases, query authoring, stored procedures, end-to-end data pipeline development.
• Experience performing operational analysis on internal and external data and processes to uncover failure points and identify opportunities for improvement.
• Strong analytic skills related to working with complex, multi-layered data pipelines and dependent datasets.
• Experience facilitating calls to capture end-user requirements with technical and non-technical users.
• Holistic awareness of processes supporting data preparation, metadata, dependencies, lineages, compliance and workload management.
• Understanding of data modeling concepts: conceptual, logical, relational and dimensional/multi-dimensional modeling.
• Understanding of meta-model and metadata management requirements.
• Experience with data structures/interfaces for applications and business processes.
• Experience with Microsoft Fabric: pipelines/notebooks/Lakehouse/Medalion architecture
• Experience with data pipeline tools such as SSIS and Azure Integration Services
• Experience using orchestration tools such as ActiveBatch
• Experience with web services and API integrations
• Experience with scripting languages such as Python and PowerShell
• Experience with Agile, DevOps and DataOps methods and technologies (Source Code Control, Versioning, Test Automation, CI, CD, Telemetry)
• Commitment to confidentiality and data security
• Strong communication and client-facing skills
• Ability to work with external and internal clients and maintain attendance

Responsibilities

• Design, implement and maintain robust, efficient data pipeline architecture.
• Identify and implement internal process improvements to automate and scale data delivery.
• Build and maintain service-based architecture for publication of data objects.
• Collaborate with data architects and analysts to evolve the data environment.
• Support data-related issues for Business and IT stakeholders.
• Develop frameworks and guidelines to ensure data structures are accurate, compliant and secure.
• Establish data quality and protection standards across the enterprise.
• Define performance and quality metrics and ensure compliance with policies.
• Participate in on-call rotation to monitor and resolve data integration alerts.

Skills

SQL

Data pipelines

Data modeling

Python

PowerShell

Azure

SSIS

Azure Integration Services

ActiveBatch

Web services/API

Tools

MS SQL Server

Microsoft Fabric

Azure Data Factory

Oracle/Relational databases

Job description

D.A. Davidson Companies is seeking a Data Engineer to expand and optimize data pipeline architecture, monitor and troubleshoot data flows, and deliver secure data provisioning. You will collaborate with software teams, DBAs, data analysts and end users on complex data initiatives to ensure best-practice delivery.

The role emphasizes building scalable pipelines, maintaining data quality, and supporting data-related technical issues for stakeholders across the firm.