Manager - Data Engineering at Smiths Group

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

05 Aug, 26

Salary

0.0

Posted On

07 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Team Leadership, Cloud Platforms, SQL, Python, PySpark, ETL/ELT, Data Lake Architecture, Data Modeling, Big Data, CI/CD, Data Governance, Power BI, SAP Integration, Salesforce Integration, AI/ML Architecture

Industry

Security and Investigations

Description

Company Description Every minute of every day, Smiths Detection’s threat detection and security screening technology helps to protect people and infrastructure, making the world a safer place. Smiths Detection is a global leader in the development, manufacture and management of security and detection solutions designed to make the world a safer place. Our technology provides threat detection and screening solutions for customers in our key markets: aviation, ports and borders, defence, and urban security. Our expertise spans 21 global offices, seven manufacturing sites and five R&D centres, with a global network of 3,000 dedicated colleagues contributing towards over 40 years at the frontline of advances in safety and security. This results in careers built on variety and the opportunity to work on a range of state-of-the-art solutions, where you can develop your knowledge and experience every day. Job Description Duties / Key Responsibilities: Supervise and manage a team of Data Engineers, providing technical guidance, mentorship, performance review and support for professional development. Own the Data Lake architecture setup, maintenance, and optimization across the enterprise platform. Lead the design and implementation of data ingestion, transformation, and integration pipelines, including ETL/ELT workflows across enterprise systems such as SAP and Salesforce. Ensure compliance with data governance, privacy, and security standards in alignment with organizational policies. Define and implement data engineering best practices, including version control, CI/CD, performance tuning, and automation across all delivery activities. Oversee data quality frameworks, validation rules, and monitoring processes to ensure accuracy and consistency across the platform. Supervise migration and modernization initiatives for the data lake, ensuring seamless transitions and minimal disruption. Collaborate with Data Architects, Analytics teams, and IT stakeholders to deliver scalable technical solutions and analytics-ready data models. Monitor data platform resource usage and support cost-optimization efforts across cloud infrastructure while maintaining system performance and reliability. Contribute to the design of AI- and ML-ready data architecture and support the development of the data strategy and platform roadmap in collaboration with senior leadership. Qualifications Technical Knowledge and Skills: Must Have Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field. 8-12 years of Data Engineering experience, with 3-5 years in a leadership or managerial role. Expertise in at least one major cloud platform: Azure (Data Lake, Databricks, Synapse, Data Factory), AWS (S3, Glue, EMR, Redshift), or GCP (BigQuery, Dataflow, DataProc). Strong proficiency in SQL, Python, and PySpark for ETL, data transformation, and automation. Experience with Big Data technologies (Hadoop, Spark) and modern data lake house architectures. Proficiency in dimensional and relational data modeling (Star, Snowflake schemas) with metadata management. Experience integrating data from on-premise systems, REST APIs, and third-party sources (SAP, Salesforce). Working knowledge of Power BI and data security frameworks, governance, and compliance best practices. Proven ability to lead distributed teams and manage project deliverables. Experience in budget planning and cost optimization for cloud infrastructure. Exposure to AI/ML frameworks and cloud-native AI services (Azure OpenAI, Amazon Bedrock, Google Vertex AI). Proficiency in English (spoken and written). Preferred Qualifications: Certification in Azure DP-203, AWS Data Analytics Specialty, or GCP Professional Data Engineer. Experience in global, multi-system, or large-scale data environments. Exposure to real-time or streaming data tools (Kafka, Event Hubs, Stream Analytics). Background in manufacturing or engineering organizations. Experience supporting data science or predictive analytics initiatives. Competencies and Abilities: Strong leadership, team-building, and mentoring capabilities. Excellent analytical thinking, problem-solving, and attention to detail. Strategic thinker with hands-on execution approach. Strong communication and stakeholder management skills across business and technical teams. Organized, systematic, and capable of managing multiple priorities under pressure. Self-motivated, reliable, and passionate about innovation and continuous improvement. Additional Information Join us and we’ll help build your career, with excellent training and opportunities for career growth across the business, both locally and globally. You’ll experience an inclusive environment, with strong leadership and a focus on safety and wellbeing. You’ll also have the flexibility to choose from a wide range of benefits to suit your lifestyle, offering you and your family support from a health and wellbeing, financial and lifestyle perspective. Join us and work for a world-leader, with the benefits and training to reward your dedication and skills. Be part of a team where we are making the world a safer place. We believe that different perspectives and backgrounds are what make a company flourish. All qualified applicants will receive equal consideration for employment regardless of color, religion, sex, sexual orientation, gender identity, national origin, economic status, disability, age, or any other legally protected characteristics. We are proud to be an inclusive company with values grounded in equality and ethics, where we celebrate, support, and embrace diversity. At no time during the hiring process will Smiths Group, nor any of our recruitment partners ever request payment to enable participation – including, but not limited to, interviews or testing. Avoid fraudulent requests by applying jobs directly through our career’s website (Careers - Smiths Group plc) Grade: 13 Employee Group: Permanent Global Region: Asia Pacific

Responsibilities

Supervise a team of data engineers to design and optimize enterprise data lake architectures and ingestion pipelines. Collaborate with stakeholders to implement data governance, quality frameworks, and AI-ready data strategies.