Technical Lead - (Azure/AWS/GCP)

Job description

The purpose of this role is to maintain, improve, clean and manipulate data in the business’s operational and analytics databases. The Data Engineer works with the business’s software engineers, data analytics teams, data scientists and data warehouse engineers in order to understand and aid in the implementation of database requirements, analyse performance, and troubleshoot any existent issues. Job Description: Business Title Data Engineer-Technical Lead Years of Experience Min 6 and max upto 10. Job Description: Technical Lead with strong hands‑on experience in cloud-based data platforms (AWS, Azure, GCP) to design, develop, and optimize scalable data solutions. This role focuses on building robust data pipelines, implementing modern data platforms, contributing to solution designs, and supporting pre‑sales and client discussions. The ideal candidate is a seasoned developer who can work independently on complex data engineering problems while collaborating closely with architects, stakeholders, and junior engineers. Must have skills: Core Technical Skills 7–10 years of hands‑on experience in data engineering and development roles. Strong hands-on experience with AWS and/or Azure and/or GCP data services such as BigQuery, Synapse, Redshift, Databricks, etc. Any 2 cloud experience is mandatory. Solid expertise in data modeling, ETL/ELT pipeline development, data warehousing, and lakehouse architectures. Strong Python development skills for data engineering, automation, orchestration, and solution prototyping. Extensive experience working with SaaS-based data platforms (e.g., Databricks, Snowflake, managed analytics services). Experience implementing and integrating Master Data Management (MDM) solutions such as Informatica, Reltio, Profisee, or equivalent tools. Practical knowledge of data governance, security, access control, and compliance requirements in cloud environments. Basic exposure to Agentic AI concepts, such as AI-driven automation, data orchestration, or intelligent workflow augmentation. Ability to design, build, and optimize scalable and high-performance data pipelines. Experience in query optimization, performance tuning, and cost optimization across cloud data platforms. Hands-on experience supporting analytics, BI, and downstream consumption layers. Strong verbal and written communication skills to effectively collaborate with architects, QA, DevOps, and business stakeholders. Ability to explain complex technical concepts clearly to non-technical audiences. Good to have skills: Familiarity with AI/ML integration into data platforms and analytics workflows. Prior experience working in a consulting or professional services environment. Key responsibilities: Design, develop, and maintain robust, scalable, and secure data pipelines and platforms across AWS, Azure, and GCP. Write high-quality, maintainable code in Python and SQL; implement ETL/ELT processes and data transformations. Collaborate with solution architects to implement approved data architectures and provide development-level design inputs. Support pre-sales efforts by contributing to technical inputs, building PoCs, demos, and solution prototypes when required. Implement data quality checks, governance standards, security controls, and compliance requirements in developed solutions. Work closely with cross-functional teams to understand requirements and translate them into effective technical implementations. Guide and mentor junior developers, conduct code reviews, and promote best practices within the team. Stay current with emerging cloud, data engineering, and AI technologies and recommend improvements to existing platforms. Education Qualification: 1. Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field. Certification If Any -AWS Data Analytics / Solutions Architect Azure Data Engineer Associate GCP Professional Data Engineer Any two of the above Databricks, Snowflake, or other cloud data platform certifications are a plus. Shift timing 12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone Location: DGS India - Pune - Kharadi EON Free Zone Brand: Merkle Time Type: Full time Contract Type: Permanent