Job description

Responsibilities: Lead the design and implementation of robust, scalable, and secure data architectures, including data lakes, warehouses, and pipelines. Stay ahead of emerging trends and technologies in data engineering and architecture. Provide thought leadership in data modeling, storage, and processing frameworks. Guide and mentor data engineers and analysts, promoting best practices and high standards in data design and governance. Drive continuous improvement in data performance, including query optimization, latency reduction, and efficient resource utilization. Define and enforce data security measures to protect sensitive information, ensure compliance with privacy regulations (e.g., GDPR, HIPAA), and prevent unauthorized access. Ensure high-quality, maintainable data solutions using industry standards. Conduct and review data models and ETL code to uphold consistency and best practices. Analyze complex technical challenges in data environments and develop innovative, scalable solutions. Requirements: 10+ years of experience in data architecture, engineering, or analytics, from design to implementation. Extensive experience with data platforms such as Snowflake, Azure Synapse, Google BigQuery, or AWS Redshift. Deep understanding of data modeling techniques (e.g., star schema, snowflake schema, normalized/denormalized models) and data governance frameworks. Proficient in building and managing ETL/ELT pipelines using tools like Apache Airflow, Azure Data Factory, Talend, or Informatica. Experience integrating data systems with cloud platforms (AWS, Azure, GCP) and APIs using tools like Mulesoft, Azure Functions, or API Management. Familiarity with CI/CD tools and automation workflows for data, such as Azure DevOps, GitHub Actions, and infrastructure management using Terraform. Experience with data monitoring and observability tools like Datadog, Splunk, or Azure Monitor. Strong understanding of data storage strategies, including relational databases (SQL Server, PostgreSQL), NoSQL (MongoDB, Cassandra), and file-based systems (Parquet, Avro). Excellent verbal and written communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders. Customer Communication: Actively listen to client needs and translate them into scalable data solutions. Communicate technical ideas clearly and build lasting relationships based on trust and delivery. Keep stakeholders informed on progress, issues, and resolution plans. Stakeholder Management: Identify key stakeholders and manage expectations effectively. Resolve conflicts diplomatically and align stakeholders with product and technical goals. Promote change management and ensure transparent communication throughout. Cross-Functional Team Coordination: Collaborate with analytics, engineering, QA, and DevOps teams to ensure smooth execution. Align multi-disciplinary teams towards shared milestones. Ensure clarity of data requirements across the product development lifecycle. Preferred Qualifications: Experience implementing Agile methodologies (Scrum, Kanban) using tools like JIRA and Confluence. Experience with data cataloging and lineage tools like Collibra, Alation, or Microsoft Purview. Familiarity with data accessibility standards, data quality frameworks, and test automation for data pipelines. Compensation, Benefits and Duration Minimum Compensation: USD 62,000 Maximum Compensation: USD 217,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees. This position is available for independent contractors No applications will be considered if received more than 120 days after the date of this post #J-18808-Ljbffr

Requirements