Lead Data Engineer
2 days ago
At INDI, we're passionate about empowering individuals and businesses worldwide. Our cutting-edge recruiters connect leading companies with top talent, fostering a dynamic environment where innovation thrives. Join us in shaping the future of work.
Overview of the role:
The Lead Data Engineer position focuses on serving as core contributors to internal Data Platforms, responsible for building scalable, resilient pipelines that support Business Operations, Analytics, and cutting-edge AI/ML initiatives. This role involves designing, implementing, and optimizing data pipelines using a wide range of Big Data and cloud-native technologies while providing technical leadership, guiding personnel, and ensuring architectural consistency across projects.
Key responsibilities:
Providing technical leadership and mentorship to other data engineers, helping them develop and succeed in their roles.
Leading design reviews, enforcing coding standards, and guiding architectural decisions to ensure platform scalability and maintainability.
Partnering with senior stakeholders and engineering leadership to prioritize and plan technical work that aligns with strategic business goals.
Acting as technical points of contact for cross-team collaborations, participating in project planning, scoping, and retrospectives.
Demonstrating curiosity, initiative, and capability to integrate AI-powered tools into day-to-day engineering workflows.
Supporting AI/GenAI projects by building pipelines that feed LLM apps and recommendation systems.
Driving adoption of data engineering best practices across organizations, including testing, CI/CD, and observability.
Designing, building, and maintaining batch and streaming data pipelines using native data platforms.
Ingesting data from various sources, including REST APIs, cloud services, and enterprise SaaS platforms.
Implementing robust transformation logic using Python, PySpark, SQL, and Java across structured and semi-structured datasets.
Ensuring data integrity, lineage, and performance across ingestion, transformation, and delivery layers.
Requirements:
Data Engineering Experience: Substantial background (6+ years) as Data Engineer in enterprise-scale data infrastructures.
Leadership Skills: Proven leadership in technical project management and personnel mentorship.
Architectural Guidance: Track record of guiding architectural conversations in high-throughput data ecosystems.
Programming Mastery: Advanced proficiency in SQL and Python programming, with expertise in PySpark or Java.
Data Architecture: Comprehensive knowledge of data modeling, transformation methodologies, and data warehouse architectures.
Hadoop Ecosystem: Proven expertise with Hadoop ecosystem technologies.
Pipeline Development: Successful implementation of resilient, high-performance data pipelines meeting strict service level agreements.
Integration Expertise: Deep understanding of API integration, performance optimization, and data schema adaptation.
Language Proficiency: Advanced level of English.
Additional skills preferred:
Workflow Tools: Practical implementation experience with Apache NiFi and Apache Airflow.
Development Environment: Expertise in containerized environments, developer tooling, and API frameworks.
AI/ML Platforms: Demonstrated capabilities in AI/ML platform support and generative AI pipeline development.
Innovation Contributions: Proven contributions to internal technological innovations within data engineering workflows.
What to expect from us:
Competitive Compensation: Excellent payment in USD or your preferred local currency.
Paid Leave: Parental leave, vacation, and national holidays.
Dynamic Work Culture: Innovative and multicultural environment.
Elite Collaboration: Work with the global top 1% of talent.
Growth and Support: Mentorship and career development opportunities.
If you are interested in being part of a team composed of the best professionals and working 100% goal-oriented in an innovative environment, do not hesitate to apply
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