Description & Requirements
What Makes Us a Great Place to Work
We are proud to be consistently recognized as one of the worlds best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the #1 consulting firm on Glassdoor’s Best Places to Work list, and we have maintained a spot in the top four on Glassdoors list for the last 12 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents.
Who Youll Work With
Bains Next-Generation Software Solutions (NGSS) team has been set up to help Industry and Capability Practices digitize their Intellectual Property through a diversified set of technology, services, and support.
The team supports practices, case teams, and clients through various product delivery models including best-in-class partnerships with leading SaaS vendors, product development using industry-leading low code and business engineering platforms, and developing highly complex custom software solutions and products.
Bain’s Private Equity Group (PEG) is the leading consulting partner to the private equity industry and its key stakeholders, with a global practice more than three times larger than any competitor. Our network of more than 1,000 experienced professionals serves private equity and institutional investor clients across the investment life cycle, from deal generation and due diligence to portfolio value creation and exit planning.
What Youll Do
We are developing a suite of data and software products to transform how the private equity industry, one of the less digitalized industries historically, obtains and consumes data to generate key investment insights.
As the Lead Engineer, Data Architecture and Engineering, you will play a pivotal role in development of PEG’s cutting-edge big data aggregation and analytics platform and user applications that help investors answer questions in the private equity investment process. You will work under the guidance of the team’s Principal architect across a broad range of data related responsibilities.
The primary tasks of this role revolve around core product development including working as part of a cross-functional Agile development team to understand the business context and product domain, designing the underlying data model/schema to meet the product’s functional and non-functional requirements, ensuring the data architecture scales and remains performant based on the expected volumes and usage patterns, is consistent and has the right enforcement and integrity checks, implementing the data model using scripts/automation, working with the team to test and validate the design, and updating the model as needed to support new and changing business requirements and product features.
This role will also setup automated data ingestion pipelines with 3rd party providers, internal datasets, and clients to continually refresh a product’s underlying structured and unstructured dataset. This will involve working with a combination of enterprise-level data ingestion and integration platforms, cloud-native services, and custom scripting and programming.
Another part of the role will revolve around delivery, partnering with Bain’s Private Equity Practice and case teams to successfully deploy the product at Bain’s clients. This will involve working to procure the required data from clients and case teams, using industry-leading tools and platforms to validate/cleans/blend/transform the data into the required product-specific schema, uploading the data into the tool, and running final validation checks.
Product Development, Support, and Maintenance
- You will own the end-to-end data model/schema design, implementation, and support for Private Equity products across the portfolio
- You will work with the Next Gen team’s Senior Architects and Engineering Managers to validate designs, discuss trade-offs and benefits of various approaches, and ensure long-term scalability and performance over time as data volumes and user concurrency grows with product adoption
- You will ensure data models follow all Next Gen and industry-standard best practices related to data security, normalization, naming conventions, primary/foreign key relationships, indexing, constraints, and other considerations
- You will work with Bain and Next Gen’s Cloud and Operations teams to ensure best practices and standards are followed related to infrastructure/hosting, data security, user access management, permissions, monitoring, patching, and logging/auditing
- You should create approved and agreed-upon data models using DDL scripting to ensure repeatability and consistency, maintain scripts in a version control system
- After data model creation, you will work to validate/test the model to ensure it meets all product and business requirements including creating realistic sample data sets, ensuring product queries and DDL statements run within expected values, run explain plans to ensure queries follow optional execution paths, and data remains consistent over time
- During the course of product development, You will work as part of the core engineering team to update and test the data schema as needed to support new requirements and updates
- You will design and implement large scale data pipelines that take data in from a variety of sources (cloud storage, flat files, APIs, etc.), run various cleansing/validation processes, and output the data in a defined format for product usage.
- You will design, implement, maintain large scale data integration solutions using fuzzy logic, text analytics, and heuristics leveraging graph and distributed compute technologies
- You will design, implement, maintain complex knowledge graphs of mixed data types; run scalable analytics on these knowledge graphs and support / coach other engineers and data scientists in querying knowledge graphs
- You will design and implement frameworks to version and track evolution of knowledge graphs over time; enable time-series analytics of the knowledge graph in the long run
- You will design and implement pipelines to continuously improve data quality through live feedback from end-user applications or human-in-the-loop QA and data integration mechanisms for data quality teams to use
- You will work as part of a cross-functional Bain team to successfully deploy Next Gen / Private Equity products with clients
- You should define, document, and communicate required data schemas formats for products and collection requirements for case teams/clients
- You will work with Bain and clients on defining the expected data set sizes, including initial load, cadence of new data imports, and long-term sizing of data based on usage assumptions
- You will work to procure required data from client systems using a variety of protocols including APIs, direct database connections, SFTP, cloud, flat files, and others
- You should use industry-leading data/ETL tools for data preparation including data validation, cleansing, joins/mergers, and reformatting into product required schemas for import
- You will upload data into product databases, ensuring data accuracy, consistency, and integrity
- You should keep up-to-date on various technologies related to data architecture and engineering
- You will want to participate on technical discovery, POCs, and innovation work streams to validate new tools, technologies, and designs
- Training, professional development, internal meetings, team building events/outings, etc.
- Strong experience with traditional relational database management systems (e.g., SQL Server, MySQL, PostgreSQL, Oracle) and SQL skills (DML & DDL)
- Experience with graph databases (e.g., Neo4j, ArangoDB, AWS Neptune) and related query languages (e.g., SPARQL, Cypher)
- Strong experience in data integration, entity linking, also known as named-entity linking (NEL), on sparse, external datasets (e.g., web crawling, 3rd party company databases)
- Strong relational and non-relational data modelling and design skills (tables, relationships, PK/FK, constraints/indexes)
- Experience using distributed compute technologies (e.g, Apache Spark, Apache Flink) in ETL and ELT workloads and data integration
- Strong experience creating custom user defined functions, procedures, views, materialized views, and optimized queries
- Ability to troubleshoot slow performing queries, examining indexes, and running explain plans
- Experience designing, implementing, and supporting end-to-end automated data pipelines using enterprise tooling, cloud-native services, or custom coding/development
- Strong communication and presentation skills, including documenting complex data flows and processes for long-term support and maintenance
- Must be result-driven, be an analytical and creative thinker, be self-motivated and proactive, be highly organised and demonstrated ability to stay calm and composed in a fast-moving environment
- Entrepreneurial spirit, innovative mind-set, willing to try new things, think outside the box, test and learn attitude
- Experience designing, implementing, maintaining complex enterprise or web knowledge graphs over time
- Experience with NoSQL databases (e.g., MongoDB, AWS DynamoDB) and cloud-native data warehouses (Snowflake, AWS Redshift, Azure Synapse, Databricks)
- Experience working with main 3rd party company and deal datasets (e.g., S&P Capital IQ, BvD, D&B, ZoomInfo, Dealogic, etc…)
- Python coding and development experience
- Experience with cloud-native data services (e.g., AWS Glue, Azure Data Factory)
- Experience with Big Data technologies, stream processing/ computation, data virtualization, data logistics (e.g. Apache Flink, Kafka, Nifi, Presto)
- Knowledge of Data Science methodologies
Bain & Company is the management consulting firm that the world’s business leaders come to when they want results. Bain advises clients on strategy, operations, information technology, organization, private equity, digital transformation and strategy, and mergers and acquisition, developing practical insights that clients act on and transferring skills that make change stick. The firm aligns its incentives with clients by linking its fees to their results. Bain clients have outperformed the stock market 4 to 1. Founded in 1973, Bain has 58 offices in 37 countries, and its deep expertise and client roster cross every industry and economic sector.