Data Engineering Lead

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence. Job Title: Data Engineering Lead Job Summary: We are seeking an experienced Data Engineering Lead to oversee and guide our organization's data engineering function. The ideal candidate will combine deep technical expertise in big data and data engineering with strong leadership skills to drive innovation, best practices, and excellence across our data engineering teams. Key Responsibilities: Establish and evolve the strategic direction for the data engineering practice across the organization. Define and implement best practices, standards, and methodologies for data engineering processes and technologies. Lead the design and architecture of scalable, enterprise-wide data solutions and platforms. Oversee multiple data engineering teams and projects, ensuring alignment with organizational goals and technical standards. Mentor and develop data engineering talent across the organization, fostering a culture of continuous learning and innovation. Collaborate with other practice leads and senior leadership to align data engineering initiatives with broader technology and business strategies. Stay abreast of emerging trends and technologies in data engineering and feature engineering, evaluating their potential impact and guiding adoption where appropriate. Drive the selection, implementation, and optimization of data engineering tools and technologies. Oversee the design and implementation of data pipelines, ETL processes, and data integration solutions. Establish KPIs and metrics to measure the effectiveness and efficiency of data engineering practices. Represent the data engineering practice in executive-level meetings and decision-making processes. Oversee the design and implementation of data pipelines, ETL processes, and data integration solutions. Guide the adoption of cloud-based data solutions and migration strategies. Participate in industry events, conferences, and communities to enhance the organization's reputation in data engineering. Required Qualifications: 10+ years of experience in data engineering roles, with at least 3 years in leadership positions Deep expertise in big data technologies, cloud platforms, and data integration tools and programming languages such Scala, PySpark with Spark knowledge. Strong understanding of data governance, security, and compliance requirements Proven track record of successfully leading large-scale data engineering initiatives Excellent communication skills with the ability to convey complex technical concepts to both technical and non-technical audiences Strong leadership and mentoring abilities with experience managing and developing teams Experience in establishing or significantly growing a data engineering practice Knowledge of machine learning and AI technologies and their integration with data engineering Familiarity with Agile and DevOps methodologies Relevant industry certifications (e.g., AWS Certified Big Data, Google Cloud Professional Data Engineer, Databricks, Snowflake) Experience in a consulting or professional services environment Published articles or speaking engagements related to data engineering and/or feature engineering Good knowledge on GraphDBs, VectorDBs and building RAG frameworks. Preferred Qualifications Certifications: Snowflake SnowPro Certification or Databricks Data Engineer Professional. Scripting Languages: Experience with Python or other scripting languages for automation and data processing. Industry Experience: Familiarity with industries such as manufacturing, oil & gas, or automotive is a plus. Why Ascentt? Innovative Projects: Work on cutting-edge data solutions that drive business transformation. Collaborative Environment: Join a team of professionals who value collaboration and continuous learning. Career Growth: Opportunities for professional development and advancement within the company. PI b4c1df-