Position Summary:

The Senior Lead Data Solutions Engineer is responsible for leading the delivery, managing and operationalizing data solutions pipelines in support of data and analytics use cases using appropriate methodologies, technologies including extract, transform and load of data. As Lead, Sr. Data Solutions Engineer, you will have responsibility for leading Data solution design for enterprise data and analytics. In addition, you will provide technical and thought leadership, emerging technology evaluation, and mentorship. The Senior Lead Data Solutions Engineer is also responsible for recommending The Senior Lead Data Solutions Engineer develops and improves standards and procedures to support quality development, testing, and production support. The role is expected to drive/lead the delivery of one or more data solution components from project inception through its delivery in close collaboration with cross-team members.

Essential Duties and Responsibilities:

• Lead data engineering development projects which include the design of complex flexible, durable, reusable and scalable data pipelines and frameworks to automate the ingestion, processing and delivery of both structured and unstructured batch and real-time streaming data employing a variety of data integration and data preparation tools for on premises and cloud for different business scenarios.

• Lead collaborative team working with other areas to ensure that all solutions are complete, operable, conform to business processes, and meet the business needs with the agreed quality of service

• Evaluates ETL/ELT best practices within the industry to learn principles and applications and drive development adoption and trains others

• Evaluates the effectiveness of data integration tools and assist in platform discussions and decisions

• Evaluate, design, build refine data and analytics capabilities

• Lead the technical roadmap for the enterprise analytics capabilities engineering

• Coach and mentor a team of data solution engineers

• Communicate the technical dependencies to the concerned teams and establish coordination for seamless implementation of the individual components

• Design robust data solutions in support of enterprise data solutions engineering

• Help craft and execute enterprise data engineering strategy

• Recommends improvements to data architecture processes to ensure high quality of data architecture deliverables and consistency.

• Solves complex issues in target data architecture design processes (e.g. data management process modeling, data entity matrix design).

• Ensure the end-to-end solution is fit for purpose, meet the needs of business, the agreed requirements, and are both pragmatic and supportive of the strategic architecture direction

• Monitors data architecture design processes (e.g. interface to data), in accordance with existing processes and standards.

• Develops standards, processes and methodologies to develop each phase of data architecture (e.g. data manipulating processes, database technology

Financial Responsibilities

• Significant understanding of effort estimation activities. Will lead large/complex estimation activities.

• Drives expectations in meeting deadline within budget, schedule and appropriate quality.

Qualifications:

• Bachelor or Master of Science in Engineering, Computer Science, Information Technology or equivalent

• 10+ years of data warehousing, big data, data engineering, and other related specialization

• Expertise in cloud providers (Azure, AWS, or GCP) preferably with Azure

• Expertise in cloud data technologies such as Snowflake, Synapse, but preferably in Databricks Lakehouse

• Expertise in Data Integration tools

• Expertise in large scale data solution architecture

• Experience working with large scale projects

• Experience working with business and technical stakeholders

• Must be able to perform complex tasks and handle multiple priorities, and can perform exceptionally under high stress conditions.

• Must be capable of fully articulating concisely technical concepts to non-technical audiences.

Knowledge and Skills:

• Extensive ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.

• Extensive experience with popular database programming languages including SQL, PL/SQL, T-SQL, others for relational databases

• Extensive experience in one of the following tools: Informatica, ADF or Talend

• Extensive experience with database technologies: Oracle, MSSQL, Hadoop and NoSQL

• Extensive experience with various Data Management architectures like Data Warehouse, Data Lake and the supporting processes like Data Integration, Governance, Metadata Management

• Extensive experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include [ETL/ELT, data replication/CDC, message-oriented data movement] and data ingestion and integration technologies such as stream data integration, and data virtualization.

• Extensive experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production

• Extensive experience writing and optimizing advanced SQL queries in a business environment with large-scale, complex datasets

• Extensive experience of data warehousing and data lake best practices within the industry

• Extensive experience of various development and deployment environments on-premises, in the cloud and across multi-cloud environments such as: AWS, Azure, Google

• Extensive experience and hands-on experience with scripting languages: Python, Scala, Java, etc …

Physical Demands:

• The physical demands described here are representative of those requirements employees must meet to perform the essential functions of this job with or without reasonable accommodations. While performing job functions the employee is regularly required to sit, stand, write, review and type reports, compile data, operate a pc, communicate, listen, and assess information. The employee may move about the office complex, may travel to other office locations and may lift, push, pull or move 10 - 15 pounds. Visual requirements include distant, close and color vision, and ability to adjust focus.

Work Environment:

• The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of the job. The environment includes work inside/outside the office.

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