MARSLYTICS

Data Engineer We are seeking a skilled Data Engineer to join our Process Improvements and Technology team. This role will play a crucial part in this exciting time of our company’s exponential growth. The ideal candidate is hard-working and excited by the prospect of optimizing, owning, and growing the team’s data architecture to support the ongoing data projects and data product development! As our Data Engineer you will support the cross-functional analytics team – which is comprised of executives, data analysts, and data scientists – across multiple initiatives and will ensure efficient data delivery is standardised across the team’s data warehouse. What you'll be doing: Crafting and maintaining efficient data pipeline architecture Assembling large, complex data sets that meet functional / non-functional business requirements Identifying, crafting, and implementing internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Building the infrastructure required for efficient extraction, transformation, and loading (ETL) of data from a wide variety of data sources using SQL and ‘big data’ technologies Working with technical and non-technical stakeholders to assist with data-related technical issues and support their data infrastructure needs Working with the team to strive for clean and meaningful data, and greater functionality and flexibility within the team’s data systems What you bring to the table: 2+ years of experience in a data engineering role BTech in computer science or equivalent Advanced working SQL knowledge, query authoring, database optimization, and experience working with relational databases Experience with object-oriented/object function scripting languages: SQL, Python, R, Scala, etc Strong project management and organizational skills Experience supporting and working with cross-functional teams in a dynamic environment Experience building, maintaining, and optimizing data pipelines, architectures, and data sets Experience cleaning, testing, and evaluating data quality from a wide variety of ingestible data sources Design processes supporting data transformation, data structures, metadata, dependency, and workload management Experience with manipulating, processing, and extracting value from large, disconnected datasets including structured, semi-structured and unstructured data Experience with Azure, AWS or Google GCP cloud services Preferred experience with data platforms/tools: Databricks, Azure Synapse Analytics, Azure Data Lake Storage.