Lead Data Engineer

Overview

Wolf & Company is a leading advisory and consulting firm, delivering high-impact financial, compliance, and technology services. Our Wolf Data Solutions division, including InsightOut, is at the forefront of data transformation, helping organizations streamline data management, optimize analytics, and implement AI-driven insights.

 

We are seeking an exceptionally skilled and experienced Lead Data Engineer to play a pivotal role in shaping the architecture, development, and execution of complex data engineering projects. This individual will be responsible for designing scalable data pipelines, architecting enterprise-grade solutions, and leading a high-performance engineering team. If you are a technical leader, hands-on problem solver, and data innovator, we want to hear from you!

 

Responsibilities

Data Architecture & Engineering Leadership

• Lead the design, development, and optimization of scalable data architectures, including data lakes, data warehouses (EDW), and real-time analytics platforms.
• Architect and implement high-performance ETL/ELT pipelines to efficiently integrate structured and unstructured data from multiple sources.
• Develop and enforce data governance, data quality, and security best practices across all data solutions.
• Design and implement data modeling strategies, ensuring efficient data storage, retrieval, and analytics performance.
• Ensure all data solutions are highly available, fault-tolerant, and optimized for scalability.

 

Advanced Data Processing & Cloud Engineering

• Build and maintain cloud-based data platforms (AWS, Azure, GCP), leveraging modern data tools and frameworks.
• Optimize data ingestion, transformation, and real-time streaming workflows using tools like Spark, Kafka, Airflow, and dbt.
• Implement data observability and monitoring tools to proactively identify and resolve data issues.

Collaboration & Technical Leadership

• Work closely with leadership, software engineers, product teams, and business leaders to define and execute data strategies.
• Serve as the technical thought leader in data engineering, guiding best practices and emerging technologies.
•  Provide mentorship and leadership to data engineers, ensuring best-in-class engineering practices.
•  Collaborate with machine learning and AI teams to deploy advanced analytics, predictive modeling, and AI-powered data products.

Performance Optimization & Automation

• Continuously improve data pipeline performance, query optimization, and cost efficiency.
• Automate data workflows, testing, and deployment pipelines to support continuous integration (CI/CD).
• Ensure data platforms meet regulatory, compliance, and security standards (SOC2, GDPR, HIPAA, etc.).

Qualifications

Technical Expertise

• 5-7+ years of experience in data engineering with a strong focus on cloud-based, enterprise-scale data solutions.
• Expertise in cloud platforms (AWS, Azure, GCP), with deep knowledge of cloud-native data services such as AWS Redshift, Snowflake, BigQuery, Azure Synapse.
• Proficiency in SQL, Python, and Spark for complex data transformations and analytics.
• Experience designing and implementing high-scale ETL/ELT workflows using Apache Airflow, dbt, or similar frameworks.
• Strong knowledge of data warehousing, dimensional modeling, and OLAP/OLTP concepts.
• Experience in DevOps practices (CI/CD pipelines, infrastructure automation, monitoring, and alerting).
• Familiarity with data lake architectures, metadata management, and cataloging tools.
• Strong API development skills, integrating data platforms with third-party services.

Leadership & Strategic Thinking

• Proven track record leading and mentoring data engineering teams, ensuring best practices and high-quality deliverables.
• Ability to translate complex business needs into technical solutions, aligning with strategic goals.
• Experience collaborating with executives, product managers, and business stakeholders to drive data initiatives.
• Exceptional ability to solve complex data challenges, optimizing for scalability, efficiency, and cost-effectiveness.
• Excellent written and verbal English communication skills – able to clearly articulate technical concepts to non-technical stakeholders.
• Ability to thrive in a fast-paced, high-growth environment with minimal supervision.
• A strong problem-solving mindset with the ability to anticipate issues before they arise.
• Collaborative team player with a strong focus on achieving business objectives