Position: Data Architect
Company: Luxoft
Experience required: 3y
English level: upper

Applying to the position, you may join one of the most respected and fastest growing institutional investors in the world. Our client is a professional investment management organization that globally invests the funds to ensure long-term sustainability. The company invests in all major asset classes, including public equity, private equity, real estate, infrastructure and fixed-income instruments, and currently has offices in Toronto, London, Hong Kong, New York, São Paulo, Luxembourg and Mumbai.
Client attracts and selects high-calibre individuals from top-tier institutions around the globe. Join our team and look forward to:
• Diverse and inspiring colleagues and approachable leaders
• Stimulating work in a fast-paced, intellectually challenging environment
• Accelerated exposure and responsibility
• Global career development opportunities
• Being motivated every day by important social purpose and unshakable principles
• A deeply rooted culture of Integrity, Partnership and High Performance
If you share a passion for performance, value a collegial and collaborative culture, and approach everything with the highest integrity, here's an opportunity.
Responsibilities:
• Manage timelines/deliverables within the team towards the successful delivery of projects.
• Deliver scalable big date solution that is in line with client's technology biases, deliver efficiency and scalability, and enable new trading activities.
• Share knowledge with team members and support staff through application demos, walkthroughs, and documentation.
Mandatory Skills Description:
• Deep technical expertise leveraging cloud technology best practices to deliver scalable big data solutions efficiently.
• Familiarity working with or building data lakes using S3.
• Familiarity in building Big Data ETL pipelines
• Exposure to big data workflows and analytics tools (Databricks).
• Experience working with big data storage (e.g. Hadoop, Cassandra, etc.).
• Proficiency with one or more programming languages: Python or Scala.
• Experience building flexible solutions that can adapt quickly to changing requirements.
• Ability to work in an entrepreneurial environment and be a self-starter.
Nice-to-Have Skills:
AWS Data Lake:
Compute & Storage options for data pipelines. Handle Upserts with s3 as storage layer; Fine Grained Access Control for parquet based object storage; Docker workings (Namespaces, CGroups, etc.), Container Security
Key AWS services/technologies including S3, EC2, Parquet EMR/Livy/Hudi, Glue, ECS, LakeFormation, RDS, Dynamo, Neptune, ElastiCache, MongoDB, Athena, DMS, Data Transfer, MWAA, RedShift, Kinesis/MSK, EBS/EFS, etc.

Big Data Processing:
Exposure to big data workflows and analytics tools (Spark/EMR/Databricks); Spark Internal architecture, performance tuning for batch jobs processing parquet data (in TB), settings for executors, readers/writers, driver (assume Yarn as the RM); Python/PySpark skills (pandas, pandas_udf, window functions, as_of joins); Tiny vs Fat Executors, OOM errors (Driver/Executor)
Ingestion patterns (Full history, vs incremental vs delta/CDC)
Languages:
English: B2 Upper Intermediate