Hi,
Good Day!




*Job Title: BigData Lead Location: initially remote 2weeks to one month
maximum & then onsite in Boston, MA  (no expenses covered) Duration:6+
Months*



*Responsibilities:*

   - Provide architectural solutions/designs to project execution teams for
   implementation.
   - Provide technology architectural assessments, strategies, and roadmaps
   for one or more technology domains.
   - Work with application developers, users, operational leadership, and
   subject matter experts to understand current and future operational data
   analysis goals. Recommend modern technology stacks to meet those goals and
   help engineering teams migrate towards their use.
   - Collaborate with the customer's operations and technology
   leadership on the future analytic goals of the organization, and design a
   technical architecture to meet those goals. Participate in configuring the
   architecture, and advise engineering teams on its efficient use.
   - Lead a work stream or act as a team lead and manage non-complex
   components of the work plan/project.
   - Utilize analytical, process, and/or technical skills to meet project
   objectives and deliverables that are self-directed and within project scope.

*Qualifications:*

   - More than 10 years of overall experience with 6 plus years delivering
   Technology solutions.
   - Experience leading and delivering complex enterprise solutions by
   directing multiple teams.
   - Experience in building and cultivating highly functioning teams
   comprised of client, and third party resources.
   - Proven track record working with and selling to the stakeholders,
   executives, and decision makers of Fortune 1000 companies.
   - Proven domain expertise with experience building business cases and
   communicating client-specific value proposition and establishing yourself
   as a trusted advisor.
   - Ability to lead technical discussions with business and technical
   decision makers, including detailing technical specifications, product
   roadmaps, deployment, and third-party integrations
   - Technical and strategic leader with deep experience and knowledge in
   the design and implementation of analytical data platforms and accepted
   best practices around data movement, meta-data
   catalogs, data governance, data transformation, data ingestion,
data security, data
   science and data mining in both Cloud, hybrid and on-premise environments.
   - Ability to design, lead and guide technical direction for data and
   analytics architecture to be in-line with business architecture and roadmap
   and analyze environments, tools, components and processes as they fit into
   the overall strategic architecture.
   - Experience in the design, implementation of data architecture and
   strategies dealing with multiple data sources and formats in a distributed
   and clustered environment for both batch and real-time environments using
   tools such as Spark.
   - Lead and implement analytical data lakes and accepted best practices
   in both AWS and hybrid cloud environments leveraging Cloudera’s Data
   platform.
   - Intimate knowledge of all phases of AWS infrastructure and concepts
   such as VPC, subnets, security groups, S3, RDS, EC2, Glacier, Lambda, IAM,
   security, encryption, DevOps, replication and disaster recovery.
   - Knowledge of Cloudera architecture and components a must including
   Director, Navigator, Manager within both cloud and on-premise environments
   including securitizing services and users with Kerberos, LDAP/Active
   Directory.
   - Deep experience with security in cloud environments around HIPAA,
   PHI/PII data, data encryption at rest and in transit as well security
   concepts like tokens, federated security models and secrets management.
   - Knowledge and familiarity with Hadoop (Hive, Impala, Presto, etc.) and
   NoSQL (HBase, Cassandra, MongoDB, etc) databases and enterprise data
   platforms such as Cloudera including security, data governance and
   discovery.
   - Knowledge of data science and analytical processes for data mining and
   predictive modeling including analytical workspaces such as Jupyter,
   Zepellin, RSudio.
   - Experience with data engineering languages such as Java, Python and
   Scala.
   - Familiarity with DevOps and CI/CD as well as Agile tools and processes
   including Git, Jenkins, Jira and Confluence.



Thanks

Ramesh

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