Tech Lead Data Engineer

About The Opportunity

We're seeking a Data Engineer to be part of a pod responsible for building, maintaining, and improving scalable data pipelines, curated data models, and data processing solutions.

Responsibilities

• Operate as a hands-on technical leader, contributing production-quality Python and SQL code while guiding engineers through solution design, implementation, testing, and delivery.
• Partner closely with client engineers, product teams, business stakeholders, and non-technical partners to clarify partially defined requirements and translate business needs into scalable technical solutions.
• Take ownership of one or more business data domains, including their pipelines, models, data quality rules, and ongoing stakeholder requests.
• Lead the onboarding and technical enablement of Data Engineers, helping them understand the architecture, development processes, business domains, and engineering standards.
• Structure and coordinate the pod’s work, distribute responsibilities, identify dependencies, and provide clear visibility into progress, risks, blockers, and technical decisions.
• Establish and promote engineering standards for data modeling, pipeline development, data quality, testing, observability, documentation, and production readiness.
• Mentor engineers, review technical solutions and code, and support the team in operating with increasing autonomy.
• Contribute to the modernization and evolution of the data ecosystem, including data architecture, processing, storage, ingestion, and pipeline technologies.
• Develop solutions that improve data quality, reliability, and observability across the data platform.
• Work in an AI-assisted engineering environment, using AI tools responsibly to improve investigation, requirements refinement, testing, documentation, and development workflows.
• Guide the team in the effective use of AI-assisted tools, ensuring that generated outputs are reviewed, validated, tested, and aligned with engineering standards.
• Identify opportunities to introduce reusable AI skills, agents, automation, and accelerators that reduce operational overhead and improve delivery velocity.
• Help simplify complex technical problems and create scalable solutions that allow internal engineers to focus on strategic initiatives.
• Contribute ideas and help shape technical investments toward impactful, data-driven outcomes.
• Be comfortable experimenting with new technologies and approaches, learning from failure, and iterating toward better solutions.

Required Qualifications

• 7+ years of professional experience in Data Engineering, including experience operating as a Tech Lead, Lead Data Engineer, or equivalent technical leadership role.
• Strong experience designing, building, and maintaining scalable data pipelines and data processing solutions.
• Advanced Python and SQL skills, with recent experience writing, reviewing, and troubleshooting production-level code.
• Strong Data Engineering fundamentals, including data modeling, data quality, pipeline reliability, distributed processing, and performance optimization.
• Experience leading technical delivery while remaining hands-on with architecture and implementation.
• Experience mentoring engineers, conducting code and design reviews, and supporting team onboarding.
• Experience taking ownership of a data domain, platform capability, or complex set of data assets.
• Experience working with cloud-based data platforms, data warehouses, and distributed processing frameworks.
• Ability to work directly with technical and non-technical stakeholders, clarify ambiguous requirements, and guide conversations toward actionable solutions.
• Strong client-facing communication skills, including the ability to explain technical decisions, risks, tradeoffs, and progress clearly.
• Proactive, ownership-oriented mindset with the ability to lead with a high degree of autonomy.
• Ability to structure work, manage dependencies, remove blockers, and maintain delivery visibility across a small engineering team.
• Ability to collaborate synchronously with teams and stakeholders based in the United States.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice To Have Skills

• Experience with Spark and cloud object storage such as Amazon S3.
• Experience with Hive, Trino, Airflow, or comparable data ecosystem technologies.
• Experience building or maintaining curated enterprise data models consumed by analytics, business intelligence, engineering, or data science teams.
• Experience with data quality frameworks such as Great Expectations.
• Experience designing data validation, write-blocking, quarantine, monitoring, or observability solutions.
• Experience with AI-assisted development tools such as Claude Code, Codex, GitHub Copilot, Cursor, or similar platforms.
• Experience building or integrating AI agents, reusable skills, or agentic engineering workflows.
• Experience introducing AI-assisted development practices and governance across engineering teams.
• Experience with modern data platform technologies such as Apache Iceberg and Databricks.
• Experience with real-time or near-real-time pipelines using Kafka, Flink, or similar streaming technologies.
• Experience leading a nearshore engineering pod or working within a managed delivery model.
• Experience supporting data platform modernization or enterprise data model refactoring initiatives.

Avenue Code reinforces its commitment to privacy and to all the principles guaranteed by the most accurate global data protection laws, such as GDPR, LGPD, CCPA and CPRA. The Candidate data shared with Avenue Code will be kept confidential and will not be transmitted to disinterested third parties, nor will it be used for purposes other than the application for open positions. As a Consultancy company, Avenue Code may share your information with its clients and other Companies from the CompassUol Group to which Avenue Code’s consultants are allocated to perform its services.