Data Architect

As a Data Engineering Lead, you will be responsible for developing and implementing data engineering projects, including enterprise data hubs or Big data platforms. Your role will involve defining reference data architecture, leveraging cloud-native data platforms in AWS or Microsoft stack, and staying updated on the latest data trends like data fabric and data mesh. You will play a key role in leading the Center of Excellence (COE) and influencing client revenues through innovative data and analytics solutions. Your responsibilities will include guiding a team of data engineers, overseeing the design and deployment of data solutions, and strategizing new data services and offerings. Collaborating with client teams to understand their business challenges, you will develop tailored data solutions and lead client engagements from project initiation to deployment. Building strong relationships with key clients and stakeholders, you will also create reusable methodologies, pipelines, and models for more efficient data science projects. Your expertise in data architecture solutions, data governance, and data modeling will ensure compliance with regulatory standards and support effective data management processes. You will be proficient in various data integration tools, cloud computing platforms, programming languages, data visualization tools, and big data technologies to process and analyze large volumes of data. In addition to technical skills, you will demonstrate strong people and interpersonal skills by managing a high-performing team, fostering a culture of innovation, and collaborating with cross-functional teams. Candidates for this role should have at least 10+ years of experience in information technology, with a focus on data engineering and architecture, along with a degree in relevant fields like computer science, data science, or engineering. Candidates should also possess experience in managing data projects, creating data and analytics solutions, and have a good understanding of data visualization, reporting tools, and normalizing data as per key KPIs and metrics. Strong problem-solving, communication, and collaboration skills are essential for success in this role.,